黑料网吃瓜爆料 has announced a strategic collaboration with Microsoft, becoming the first university in the world to give Microsoft 365 Copilot access and training to every student and colleague.
The landmark agreement will see 65,000 students, academics and colleagues benefit from the full Microsoft 365 Copilot suite, alongside training to support effective and responsible use.
This initiative forms part of the University鈥檚 wider digital and AI transformation programme, which focuses not only on tools, but on building long-term AI literacy, and ensuring the responsible integration of emerging technologies.
It will support learning, research and professional work, and graduate employability. It addresses the emerging digital divide by ensuring that all students 鈥 regardless of personal means 鈥 can benefit from advanced assistive and productivity tools.
The announcement comes 76 years after Alan Turing published his seminal 鈥楾uring Test鈥 paper while working at the University, one of the first on artificial intelligence, and reflects 黑料网吃瓜爆料鈥檚 continuing leadership in AI, with more than to understand and shape the technology.
The Microsoft 365 Copilot rollout, to be completed by summer 2026, will equip 黑料网吃瓜爆料 students with future-ready skills and enable researchers to accelerate interdisciplinary discovery and analysis at scale.
Professor Duncan Ivison, President and Vice-Chancellor of 黑料网吃瓜爆料, said: 鈥淎I is now part of everyday life. Our responsibility is not only to make these tools available to all our students and staff on an equitable basis, but to use the depth of expertise across our university to shape how AI is developed and applied for public good.
鈥淏y embracing the AI transformation early, we are working with students, colleagues and partners to maximise the benefits and manage risks responsibly. The great universities of the 21st century will be digitally enabled 鈥 this partnership represents a significant step on that journey for 黑料网吃瓜爆料.鈥
Darren Hardman, CEO, , said, 鈥淎s someone who grew up in 黑料网吃瓜爆料, I鈥檓 proud to see the University extending access to Microsoft 365 Copilot across its entire community, helping 65,000 students and staff build the skills they鈥檒l need to thrive in an AI鈥慹nabled economy. This is a powerful example of how we can pair 黑料网吃瓜爆料鈥檚 deep AI heritage with responsible, ethical adoption that helps to close the digital divide and equip people to learn, research and work more effectively.鈥
The strategic collaboration with Microsoft is one of the first major developments following the launch of the University鈥檚 new strategy, From 黑料网吃瓜爆料 for the world, demonstrating its ambition for research impact, world-class teaching and learning, and responsible leadership in digital transformation and innovation in action.
The rollout will be delivered in partnership with the Students鈥 Union, trade unions and staff networks. The University is working closely with Microsoft to ensure transparency around environmental and wider impacts, and to promote best practice in responsible and sustainable AI adoption.
Microsoft鈥檚 long-standing commitments to sustainability were an important consideration for the University in partnering with them. These include being committed to becoming carbon negative, water positive and zero waste by 2030.
Professor Jenn Hallam, Vice-President for Teaching, Learning and Students, said: 鈥淓very student deserves access to the best AI tools to enable them to thrive in their studies 鈥 no matter their circumstances or background. AI is an enabler for teaching and learning, not a replacement. It鈥檚 not just supportive in the classroom, but in wider productivity and future life skills and we鈥檙e giving students the tools and training to use it in the right way, ethically and appropriately. We鈥檙e not just preparing graduates who can go out and get good jobs, we鈥檙e preparing the next generation of citizens. That鈥檚 the mission of 黑料网吃瓜爆料 鈥 you'll get a great degree, but we鈥檒l also prepare you for a fast-changing world.鈥
Kanishka Narayan, Minister for AI and Online Safety, said: "When we bring a technology like AI together with the peerless expertise of UK universities, the potential is enormous. Whether supporting students in their studies, opening new avenues of research, or slashing the time spent on routine tasks, the benefits are transformative.
"This partnership between 黑料网吃瓜爆料 and Microsoft will help our brightest minds do what they do best 鈥 innovate. Meanwhile, initiatives like the Department for Science, Innovation and Technology's Sp盲rck Scholarships will attract high-potential AI talent to top universities like 黑料网吃瓜爆料."
]]>Interested in presenting your work at The Digital Environment Conference 2026, hosted at SISTER on 1st April 2026? We are looking for individuals to present their research in 15 minute speakers slots, or present their work on a poster board at the event.
Please email Jade at digitalfutures@manchester.ac.uk with your presentation and/ or poster title, and topic or area of research.
Please note that the open call for presentation or poster submissions deadline is Friday 27th February 2026.
Published in 1950 during Turing鈥檚 time as an academic at 黑料网吃瓜爆料, the paper was one of the first on artificial intelligence. It was in this paper that he established the Turing Test, also known as the Imitation Game, posing the question that would shape the modern world: 鈥淐an machines think?鈥
Today, more than 1,600 黑料网吃瓜爆料 researchers are designing and applying AI to tackle global challenges, transform industries, enhance public services, and improve lives. From advancing breast cancer treatment and improving menopause care to transforming crop productivity in Ghana and tackling online misogyny, 黑料网吃瓜爆料 researchers are using AI to deliver positive change for society and the environment.
To enable this, the University has invested in a world-leading research environment, creating an AI research ecosystem that supports research excellence and accelerates the journey to real-world impact. Capabilities span from the , driving the breakthroughs of tomorrow, to two dedicated units fuelling innovation - the part of , which connect partners to the University鈥檚 world-famous talent, ideas and resources.
Professor Jay adds: 鈥淲e believe AI should deliver real benefits to business, public services and society. That鈥檚 why we鈥檙e continually investing in the people, partnerships and platforms that turn bold ideas into transformative outcomes.
鈥淚n every thriving AI ecosystem, there鈥檚 a university at its heart. We鈥檙e proud to shape the future of AI 鈥 for 黑料网吃瓜爆料, the UK and the world.鈥
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]]>, co-authored by academics from the University of 黑料网吃瓜爆料 and the University of Groningen, adds nuance to the idea that journalists have hyped AI technologies. Examining AI coverage in (USA), (The Netherlands), and (Brazil) between June 2020 and September 2023. The analysis, published in the journal Digital Journalism, found that, although fascination with systems like ChatGPT was evident, the reporting often reflected deeper tensions and uncertainties about AI鈥檚 future.
Instead of merely amplifying hype, the study highlights a recurring discourse of 鈥open-ended technological inevitability鈥, according to which AI鈥檚 impact is unavoidable, though its course remains uncertain. Across all three newspapers, research revealed that ongoing power struggles among governments, corporations, experts, and citizens indicate that AI is not just a technological issue, but a political and social one.
The researchers argue that this complex media landscape may influence how AI is regulated and understood by the public, providing caution against oversimplifying journalistic coverage as mere hype.
The study introduces the concept of 鈥mediated technological drama鈥 as an alternative framework, explaining how media shapes public understanding of emerging technologies. Using theatrical metaphors, it suggests that journalists not only report on AI but also become engaged actors in the stories they tell.
For instance, a common theme across all three newspapers was comparing AI to nuclear weapons or climate impacts. These examples demonstrate the drama in action and how existential fears about AI are depicted. This multi-actor perspective is crucial for critically examining the politics behind the portrayal of emerging technologies.
The findings offer fresh insight for policymakers and media professionals seeking to navigate the evolving discourse around AI. As global conversations about regulation and ethics intensify, the role of journalism in shaping public understanding has never been more poignant.
Speaking of the findings, , Senior Lecturer in AI Trust and Security, shared:
The peer-reviewed article 鈥鈥 was co-authored by , University of 黑料网吃瓜爆料 and , from the .
]]>The University and the Santa Clara-based company have signed a Memorandum of Understanding (MoU), marking a strategic partnership aimed at leveraging the strengths of both organisations to drive advancements in AI applications across multiple sectors, including healthcare, social care, education, and sustainability.
This collaboration will provide a foundation for joint research projects, academic exchange programs, and curriculum development initiatives that will shape the future of AI-driven solutions.
Under the terms of the MoU, the partnership will focus on key initiatives, including:
Research and Development in AI, Robotics, and Automation 鈥 Exploring applications of AI in healthcare, education, and sustainability, including the development of AI-powered robotic solutions such as Fari for elderly care and Senpai for special needs education.
AI for All Initiative 鈥 Facilitating upskilling and workforce development programs in AI and robotics for healthcare, social care, and education professionals.
Joint Degree Programs and Curriculum Development 鈥 Establishing specialized programs in AI, robotics, and automation, incorporating theoretical and practical components with hands-on experience using InGen Dynamics鈥 technologies, including Fari, Senpai, and Origami AI.
Social Care Testbed Collaboration 鈥 Deploying and evaluating AI-driven robotics solutions in real-world environments to improve care delivery and assess the impact of AI in social care settings.
AI Ethics and Responsible AI Initiatives 鈥 Promoting transparency, accountability, and ethical AI development through collaborative research and policy discussions.
Global Exchange Programs 鈥 Enabling international knowledge-sharing by connecting students and researchers from the University of 黑料网吃瓜爆料 with InGen Dynamics鈥 Futurenauts initiative in India and beyond.
The collaboration will be overseen by a Steering Committee co-chaired by Professor Andrew Weightman, Professor of Medical Mechatronics the Department of Mechanical and Aerospace Engineering and Arshad Hisham, Founder & CEO of InGen Dynamics. The committee will meet biannually to define strategic roadmaps and identify new areas of mutual interest.
Mr Hisham, said: 鈥淭his partnership with 黑料网吃瓜爆料 is a significant step toward advancing AI and robotics research that has real-world impact.
鈥淏y combining our industry expertise with the academic excellence of 黑料网吃瓜爆料, we aim to accelerate innovation and create transformative AI solutions for global challenges.鈥
Professor Weightman added: 鈥淲e are excited to collaborate with InGen Dynamics to drive forward research and education in AI and automation.
鈥淭his MoU will enable us to integrate cutting-edge technology into our programs while fostering innovation that benefits society.鈥
黑料网吃瓜爆料 is globally renowned for its pioneering research, outstanding teaching and learning, and commitment to social responsibility. We are a truly international university 鈥 ranking in the top 50 in a range of global rankings 鈥 with a diverse community of more than 44,000 students, 12,000 staff and 550,000 alumni from 190 countries. Sign up for our e-news to hear first-hand about our international partnerships and activities across the globe.
]]>A 拢1m funding award from the Medical Research Council in collaboration with Innovate UK will accompany 拢1.2 million of in-kind support from 85 partners to fund the pilot phase of the UK Centre of Excellence on In-Silico Regulatory Science and Innovation (UK CEiRSI). This Centre will collaborate globally to address some of the sector's most pressing challenges and target unmet patient outcomes and safety needs.
The consortium will work with computational modelling and simulation and AI techniques鈥攁ll of which are poised to revolutionise the healthcare landscape. The UK CEiRSI will contribute to making the UK the best milieu for delivering medical innovations using in silico evidence and regulatory science.
The Centre will consist of leading universities from the UK鈥檚 four nations, world-class companies, and health systems and regulatory bodies, including the UK鈥檚 Medicines and Healthcare Products Regulatory Agency (MHRA), National Institute for Health and Care Excellence (NICE) and the Health Research Authority (HRA) but will also collaborate with colleagues in the Food and Drug Administration (FDA) in the US, and the European Medicines Agency (EMA) in mainland Europe.
Professor Alex Frangi, Bicentennial Turing Chair in Computational Medicine at 黑料网吃瓜爆料, will direct the Centre.
He said: 鈥淗uman and animal trials often face high failure rates resulting in delays, increased costs, and potential risks to patients.
鈥淥n average, pharmaceutical products take 12 years to develop, with testing consuming up to 30% of costs.
鈥淗owever, we will seek to address these critical inefficiencies by developing in-silico technologies that produce digital evidence for the digital age. Our aim is to reflect engineering practices in other sectors where physical testing is complemented by virtual testing and product optimisation. This will result in improved medical products (drugs or devices), faster and more affordable lifesaving therapies for patients, and innovative regulatory approval processes.鈥
He added: 鈥淭hese cutting-edge tools can greatly enhance reliability in testing, while substantially reducing development time and costs, as well as improving the diversity of testing conditions, leading to more equitable care.鈥
鈥淎nd that will benefit patients through reduced failure rates and recalls, while fostering economic growth by driving innovation in pharmaceuticals and medical technologies.鈥
However, despite their transformative potential, a regulatory deadlock for in-silico technologies means the technologies face barriers to adoption. Regulators lack frameworks to assess in-silico evidence, while developers hesitate to invest without clear pathways to approval.
The UK CEiRSI aims to break the deadlock and position in-silico technology and virtual trials as a mainstream approach to eliminate risk from future medical and pharmaceutical innovation developments. To tackle this impasse, the Pilot phase will implement an In Silico Airlock Initiative where actors from industry, academia and regulatory bodies will explore 10 industry-led pre-commercial regulatory pilots and assess the opportunities and limitations of current credibility frameworks.
Building on the success of a six-month discovery phase, UK CEiRSI will bring together industry leaders, regulators, Health Technology Assessment (HTA) and standardisation bodies, academics, and patient representatives - to test and refine frameworks for assessing in-silico evidence.
Reports from the project will address key issues such as regulatory frameworks, legal and ethical implications, and patient risk reduction, paving the way for in-silico technologies to make a real impact on our lives.
For more information visit:
Led by researchers at 黑料网吃瓜爆料 and 黑料网吃瓜爆料 University NHS Foundation Trust (MFT), alongside researchers in Australia and United States, the study will enable researchers to track changes in brain structure over time in children and young people with NF1.
The research is funded by a 拢2.2 million award from the US Department of Defence and is the largest investigation into brain development in NF1 to date. Using advanced machine-learning techniques, the team will analyse the brain structure of over 10,000 MRI scans, comparing them to healthy individuals of the same age.
By doing that, they will shine a light on how specific genetic changes affect the brain and how alterations in brain structure may predict learning difficulties outcomes.
The Children鈥檚 Hospital of Philadelphia, the Murdoch Research Institute in Melbourne and the Complex NF1 Service hosted by the 黑料网吃瓜爆料 Centre for Genomic Medicine at Saint Mary鈥檚 Hospital, part of MFT, which is a world leading centre for clinical care and research in NF1, have all signed up to the project.
NF1 affects approximately 1 in 2,500 children. Although the severity of the condition varies from person to person, about half of all children affected by the condition may have difficulties with learning, autism or ADHD.
Dr Shruti Garg, Senior Lecturer at 黑料网吃瓜爆料 and National Institute for Health and Care Research (NIHR) 黑料网吃瓜爆料 Biomedical Research Centre (BRC) Mental Health Theme Capacity Development Lead, is leading the international research.
Dr Garg, who is also Honorary Consultant Child and Adolescent Psychiatrist at the Royal 黑料网吃瓜爆料 Children鈥檚 Hospital, part of MFT said: 鈥淟earning and behavioural difficulties in NF1 can profoundly impact the quality of lives of affected children and young people. This funding provides a crucial opportunity for researchers to deepen our understanding of how changes in the NF1 gene impact brain development.
鈥淛ust like 鈥榞rowth-charts鈥 are widely used to monitor children鈥檚 physical growth, our research will enable us to create NF1-specific 鈥榖rain charts鈥 to serve as a reference for age-related changes in brain structure.鈥
Dr Nils Muhlert, Senior Lecturer in Psychology and Neuroanatomy at the University of 黑料网吃瓜爆料 said: 鈥淭his project is a powerful illustration of collaboration across the world, and we are tremendously excited about what it might achieve.鈥
Karen Cockburn, Charity Director of Nerve Tumours UK, said: "We fully endorse this extremely important global project, and the work of Dr Shruti Garg, who is also a member of the charity's Medical Advisory Board. This research and its potential findings will be of huge benefit for the NF1 community.鈥
Dr Grace Vassallo, Consultant Paediatric Neurologist and Clinical Lead for the Complex NF1 Service at the 黑料网吃瓜爆料 Centre for Genomic Centre for Medicine at Saint Mary鈥檚 Hospital, said: 鈥淲e are incredibly grateful for this unique opportunity to collaborate in cutting edge research into the developing NF1 Brain charts which will in future improve the clinical care for children and young people with NF1.鈥
]]>To discuss this research or potential partnerships, contact Professor Yin at hujun.yin@manchester.ac.uk.
The funding package from the University鈥檚 Strategic Investment Reserve Fund (SIRF) is being matched by 拢2 million from the Faculty itself. The investment will go towards appointing an interdisciplinary team of six senior lecturer or lecturer-level academics, six post-doctoral research associates and six PhD students. They will form a cross-cutting research cluster with the (CDTS) at the University.
The investment will also leverage further research and industry funding, and help develop new teaching and executive education programmes, strengthening the University鈥檚 capability in ethical and responsible AI.
Professor Fiona Devine, Vice-President and Dean of the Faculty of Humanities, said: 鈥淚 am absolutely delighted that the Faculty has been successful in securing this funding to significantly expand and enhance our research and teaching capabilities in this emerging field. The investment is designed to retain our status as a UK leader in cyber security and responsible AI research and teaching.鈥
Richard Allmendinger, Professor of Applied Artificial Intelligence at Alliance 黑料网吃瓜爆料 Business School (AMBS), and Faculty Associate Dean for Business Engagement, Civic and Cultural Partnerships, said: 鈥淭his investment comes at a critical juncture and gives the Faculty of Humanities a critical mass in social science-led approaches to AI which will enable us to maximise external research funding opportunities.
鈥淭he demand from industry is clear. International partners wish to collaborate on issues of AI governance and responsible AI, as do various strategic partners. As a city-region, 黑料网吃瓜爆料 also has the by number of jobs outside London.鈥
Professor Nick Lord, Director of the CDTS, and Professor of Criminology in the School of Social Sciences, added: 鈥淎I is already having a profound effect on society and will continue to do so, and that means impacting everything we do as a University, too. To mitigate risks and ensure the benefits of AI technologies we must consider the social, environmental and economic contexts they will operate in, and the consequences of their deployment.
鈥淭here is an urgent need to drive approaches to AI that are secure, safe, reliable and trustworthy. It is also vital that they operate in a way that enables us to understand and investigate when they fail.鈥
Enhancing Faculty of Humanities research power in AI trust and security will also catalyse new collaborations with the Faculty of Biology, Medicine and Health at the University, most notably with the for health technology research and innovation.
Added Professor Devine: 鈥淭he complexity and rise of data in healthcare means that AI will increasingly be applied within the field and has the potential to speed up diagnostics and make healthcare operations more efficient.
鈥Humanities research has much to contribute to this truly inter-disciplinary agenda and this investment will establish the University of 黑料网吃瓜爆料 as a leader in ethical, assessable, inclusive and responsible AI. It aligns not only with our commitment to cutting-edge research and innovation but also with our commitment to social responsibility.鈥
The AI Trust and Security team will form a cross-cutting research cluster within the CDTS. The new initiative follows the recent announcement that the University of 黑料网吃瓜爆料 was awarded the status of by the National Cyber Security Centre and the Engineering and Physical Sciences Research Council. The Centre is distinctive as it is the only cyber and digital security and trust research centre in the UK led from social science, rather than computer science or engineering.
Meanwhile, demand for new teaching programmes in the area of AI is also soaring, as demonstrated by the recent review of the .
Data from April 2020 to March 2023 shows 7,600 students have enrolled on AI and data science postgraduate conversion courses across the UK, helping to address a critical digital skills gap in the AI and data science industries.
]]>黑料网吃瓜爆料 has been awarded 拢30 million funding by the Engineering and Physical Sciences Research Council (EPSRC) for four Centres for Doctoral Training as part of the UK Research and Innovation鈥檚 (UKRI) 拢500 million investment in engineering and physical sciences doctoral skills across the UK.
Building on 黑料网吃瓜爆料鈥檚 long-standing record of sustained support for doctoral training, the new CDTs will boost UK expertise in critical areas such as advanced materials, AI, and nuclear energy.
The CDTs include:
黑料网吃瓜爆料 received joint-third most awards across UK academia, and will partner with University of Cambridge, University of Glasgow, Imperial College London, Lancaster University, University of Leeds, University of Liverpool, University of Oxford, University of Sheffield, University of Strathclyde and the National Physical Laboratory to prepare the next generation of researchers, specialists and industry experts across a wide range of sectors and industries.
In addition to leading these four CDTs, 黑料网吃瓜爆料 is also collaborating as a partner institution on the following CDTs:
Along with institutional partnerships, all CDTs work with industrial partners, offering opportunities for students to develop their skills and knowledge in real-world environments which will produce a pipeline of highly skilled researchers ready to enter industry and take on sector challenges.
Professor Scott Heath, Associate Dean for Postgraduate and Early Career Researchers at 黑料网吃瓜爆料 said of the awards: 鈥淲e are delighted that the EPSRC have awarded this funding to establish these CDTs and expose new cohorts to the interdisciplinary experience that researching through a CDT encourages. By equipping the next generation of researchers with the expertise and skills necessary to tackle complex issues, we are laying the groundwork for transformative solutions that will shape industries and societies for generations to come.鈥
Announced by Science, Innovation and Technology Secretary Michelle Donelan, this round of funding is the largest investment in engineering and physical sciences doctoral skills to-date, totalling more than 拢1 billion. Science and Technology Secretary, Michelle Donelan, said: 鈥淎s innovators across the world break new ground faster than ever, it is vital that government, business and academia invests in ambitious UK talent, giving them the tools to pioneer new discoveries that benefit all our lives while creating new jobs and growing the economy.
鈥淏y targeting critical technologies including artificial intelligence and future telecoms, we are supporting world class universities across the UK to build the skills base we need to unleash the potential of future tech and maintain our country鈥檚 reputation as a hub of cutting-edge research and development.鈥
These CDTs join the already announced . This CDT led by , Senior Lecturer in Machine Learning at 黑料网吃瓜爆料, will train the next generation of AI researchers to develop AI methods designed to accelerate new scientific discoveries 鈥 specifically in the fields of astronomy, engineering biology and material science.
The first cohort of AI CDT, SATURN CDT and Developing National Capability for Materials 4.0 CDT students will start in the 2024/2025 academic year, recruitment for which will begin shortly. 2DMoT CDT and RAINZ CDT will have their first cohort in 2025/26.
For more information about the University of 黑料网吃瓜爆料's Centres for Doctoral Training, please visit:
]]>The framework combines dimension reduction techniques and a new explainable clustering algorithm called CLASSIX, developed by mathematicians at 黑料网吃瓜爆料. This enables the quick identification of groups of viral genomes that might present a risk in the future from huge volumes of data.
, presented this week in the journal PNAS, could support traditional methods of tracking viral evolution, such as phylogenetic analysis, which currently require extensive manual curation.
Like many other RNA viruses, COVID-19 has a high mutation rate and short time between generations meaning it evolves extremely rapidly. This means identifying new strains that are likely to be problematic in the future requires considerable effort.
Currently, there are almost 16 million sequences available on the GISAID database (the Global Initiative on Sharing All Influenza Data), which provides access to genomic data of influenza viruses.
Mapping the evolution and history of all COVID-19 genomes from this data is currently done using extremely large amounts of computer and human time.
The described method allows automation of such tasks. The researchers processed 5.7 million high-coverage sequences in only one to two days on a standard modern laptop; this would not be possible for existing methods, putting identification of concerning pathogen strains in the hands of more researchers due to reduced resource needs.
, Professor of Mathematical Sciences at 黑料网吃瓜爆料, said: 鈥淭he unprecedented amount of genetic data generated during the pandemic demands improvements to our methods to analyse it thoroughly. The data is continuing to grow rapidly but without showing a benefit to curating this data, there is a risk that it will be removed or deleted.
鈥淲e know that human expert time is limited, so our approach should not replace the work of humans all together but work alongside them to enable the job to be done much quicker and free our experts for other vital developments.鈥
The proposed method works by breaking down genetic sequences of the COVID-19 virus into smaller 鈥渨ords鈥 (called 3-mers) represented as numbers by counting them. Then, it groups similar sequences together based on their word patterns using machine learning techniques.
, Professor of Applied Mathematics at 黑料网吃瓜爆料, said: 鈥淭he clustering algorithm CLASSIX we developed is much less computationally demanding than traditional methods and is fully explainable, meaning that it provides textual and visual explanations of the computed clusters.鈥
Roberto Cahuantzi added: 鈥淥ur analysis serves as a proof of concept, demonstrating the potential use of machine learning methods as an alert tool for the early discovery of emerging major variants without relying on the need to generate phylogenies.
鈥淲hilst phylogenetics remains the 鈥榞old standard鈥 for understanding the viral ancestry, these machine learning methods can accommodate several orders of magnitude more sequences than the current phylogenetic methods and at a low computational cost.鈥
]]>The highly interdisciplinary team used cutting-edge unsupervised deep learning to analyse over 50,000 three-dimensional magnetic resonance images of the heart from UK Biobank, a world-leading biomedical database and research resource.
The study, published in the leading journal , focused on uncovering the intricate genetic underpinnings of cardiovascular traits. The research team conducted comprehensive genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS), resulting in the discovery of 49 novel genetic locations showing an association with morphological cardiac traits with high statistical significance, as well as 25 additional loci with suggestive evidence.
The study's findings have significant implications for cardiology and precision medicine. By elucidating the genetic basis of cardiovascular traits, the research paves the way for the development of targeted therapies and interventions for individuals at risk of heart disease.
The research was funded by the Royal Academy of Engineering (RAEng), The Royal Society, the British Heart Foundation (BHF), and the Argentinean National Scientific and Technical Research Council (CONICET) in an interdisciplinary collaboration involving a RAEng Chair, two BHF Professors, and an IBM Fellow.
The research was directed by , Director of the , the Bicentennial Turing Chair for Computational Medicine, and a Royal Academy of Engineering Chair in Emerging Technologies. The first author was Rodrigo Bonazzola, a PhD candidate, jointly co-supervised by Prof Frangi, (CONICET, Argentina) (IBM Fellow and Chief Scientist at IBM Research).
Prof Frangi said: 鈥淭his is an achievement which once would have seemed like science fiction, but we show that it is completely possible to use AI to understand the genetic underpinning of the left ventricle, just by looking at three-dimensional images of the heart.
鈥淧revious studies have only investigated association of traditional clinical phenotypes, such as left ventricular mass or stroke volume, limiting the number of gene associations detected for a given study size. However, this study used AI not only to delineate the cardiac chambers from three-dimensional medical images at pace but also to unveil novel genetic loci associated with various cardiovascular deep phenotypes.鈥
He added: 鈥淭his research exemplifies the power of multidisciplinary teams and international collaborations, bolstered by UK Biobank's valuable data. By marrying genetic data with cardiac imaging through advanced machine learning, we've gained novel insights into the factors shaping cardiovascular health.鈥
Early career scientist and rising star, Bonazzola, the study's lead author said: 鈥淥ur research reveals genes that harbour mutations known to be detrimental to other organisms, yet the impact of common variations within these genes on cardiac structure across the human population had not been previously documented. For instance, the STRN gene, recognised for its harmful variants leading to dilated cardiomyopathy in dogs, exhibits a common variant in humans that seems to induce a subtle but detectable change in mitral orientation.鈥
Dr Ferrante said: 鈥淭he study's core achievement is a robust method based on geometric deep learning for large-scale genetic and cardiac imaging data analysis, leading to ground-breaking genetic insights related to heart structure. These discoveries could revolutionize our approach to disease understanding, drug development, and precision medicine in cardiology. The study's thorough analysis and ensemble-based methods also enhance the discovery rates and the reliability of our findings.鈥
Prof Keavney, BHF Professor of Cardiovascular Medicine at 黑料网吃瓜爆料, emphasised the transformative methodology. He said: 鈥淓mploying cutting-edge deep learning to integrate genetic and imaging data has shed light on the genetic underpinnings of heart structure. This approach is a beacon for future organ studies and understanding genetic influences on organ anatomy.鈥
Prof Plein, BHF Professor of Cardiovascular Imaging in Leeds, said: "Cardiovascular MRI plays a crucial role in understanding disease phenotypes, allowing us to uncover genetic associations that help stratify cardiovascular diseases, ultimately leading to better treatments and precision medicine."
Professor Frangi added: 鈥淥ur publication marks a significant stride in correlating deep cardiovascular imaging traits with genetic data. It paves the way for revolutionary progress in cardiovascular research, clinical practices, and tailored patient care.鈥
Professor Bryan Williams, Chief Scientific and Medical Officer at the British Heart Foundation, said: 鈥淭his new research shows the huge power of big data linking genes to heart structure. Machine learning has made this possible by transforming how we process, analyse and gain insights from big data to tackle the biggest questions in cardiovascular research. This pioneering new method has uncovered many more genes that influence the structure and function of the heart, which will lead to new insights into why abnormal structure and function can lead to heart disease.
鈥淗eart and circulatory diseases are still devastating millions of lives each year in the UK. AI could unlock more information about the genes that contribute to the structure of the heart. In future this could lead to real improvements for patients, including the development of tailored, precision treatments for people with heart problems.鈥
The paper Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology is published in
]]>The evolution of solutions is creating new opportunities to transform patient care and personal health outcomes. From remote monitoring and wearables, to artificial intelligence and machine learning, digital technologies are enabling health data collection and analysis and offering new insights, diagnosis and therapies.
Here is an overview of the Citation Impact on Digital Health Top 25 Rankings. The complete list can be accessed in 鈥檚 article.
Rank | Institution | Digital health papers in the | Citations | Percentage of papers in the top |
1 | Beth Israel Deaconess Medical Center | 70 | 1,444 | 28.57 |
2 | 51 | 532 | 17.65 | |
3 | 50 | 1,011 | 26.00 | |
4 | 75 | 1,582 | 32.00 | |
5 | 284 | 4,885 | 28.52 |
Research into digital health has grown massively nowadays, whereas the scale of growth in digital health research is remarkable. Based on Clarivate data, publications on digital health topics 鈥 which include everything from wearable devices and mobile apps to AI analytics, telemedicine and 3D printing of drugs 鈥 have risen nearly 70-fold between 2013 and 2022, from a mere 39 Web of Science-indexed papers to 2,641 鈥 while UK researchers were involved in 20 per cent of all papers.
The statistics demonstrate that the University currently has 75 digital health papers in the Web of Science, 1582 citations, 32 per cent of papers in the top 10 per cent by citation, scoring 2.50 category normalised citation impact (CNCI). It showcases 黑料网吃瓜爆料鈥檚 consistent efforts to advance digital health research that benefits the public.
Previously, the immense volumes of medical data from numerous wearable devices or mobile phones might have overwhelmed even the most data-savvy researcher. However, artificial intelligence now enables researchers to effectively navigate such vast amounts of information without requiring advanced coding skills. Likewise, hospitals and health centres worldwide are sharing patient records in a manner that allows algorithms to detect trends, including identifying emerging pandemics at their onset.
Recent University of 黑料网吃瓜爆料 research, alongside Oxford University and Cancer Research UK used Artificial Intelligence to reveal a new form of aggressive prostate cancer which could revolutionise how the disease is diagnosed and treated in the future.
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]]>A new Cancer Research UK-funded study has revealed that prostate cancer, which affects one in eight men in their lifetime, includes two different subtypes termed evotypes.
The discovery was made by an international team led by the , and 黑料网吃瓜爆料, who applied AI (artificial intelligence) on data from DNA to identify two different subtypes affecting the prostate.
The team hope their findings could save thousands of lives in future and revolutionise how prostate cancer is diagnosed and treated. Ultimately, it could provide tailored treatments to each individual patient according to a genetic test which will also be delivered using AI.
According to , prostate cancer is the most common cancer affecting men in the UK with around 52,000 cases a year. Dr Rupal Mistry, the charity鈥檚 senior Science Engagement Manager, said:
鈥淭he work published today by this global consortium of researchers has the potential to make a real difference to people affected by prostate cancer. The more we understand about cancer the better chance we have of developing treatments to beat it. We are proud to have helped fund this cutting-edge work, which has laid the foundations for personalised treatments for people with prostate cancer, allowing more people to beat their disease.鈥
The ground-breaking research, which involved additional funding from Prostate Cancer Research and involved scientists from the University of Oxford the University of 黑料网吃瓜爆料, the University of East Anglia and the Institute of Cancer Research, London, highlights how a prostate cancer diagnosis can affect physical, emotional and mental wellbeing.
Lead researcher Dr Dan Woodcock, of the Nuffield Department of Surgical Sciences at the University of Oxford, said: 鈥淥ur research demonstrates that prostate tumours evolve along multiple pathways, leading to two distinct disease types.
鈥淭his understanding is pivotal as it allows us to classify tumours based on how the cancer evolves rather than solely on individual gene mutations or expression patterns.鈥
The researchers worked together as part of international consortium, called The Pan Prostate Cancer Group, set up by scientists at The Institute of Cancer Research (ICR) and The University of East Anglia to analyse genetic data from thousands of prostate cancer samples across nine countries.
Crucially, the team's collaboration with Cancer Research UK (CRUK) aims to develop a genetic test that, when combined with conventional staging and grading, can provide a more precise prognosis for each patient, allowing tailored treatment decisions.
The researchers used AI to study changes in the DNA of prostate cancer samples (using whole genome sequencing) from 159 patients.
They identified two distinct cancer groups among these patients using an AI technique called neural networks. These two groups were confirmed by using two other mathematical approaches applied to different aspects of the data. This finding was validated in other independent datasets from Canada and Australia.
They went on to integrate all the information to generate an evolutionary tree showing how the two subtypes of prostate cancer develop, ultimately converging into two distinct disease types termed 鈥榚votypes鈥.
of 黑料网吃瓜爆料 Cancer Research Centre, who led the study, explained: 鈥淭his realisation is what enables us to distinguish the disease types. This hasn鈥檛 been done before because it鈥檚 more complicated than HER2+ in breast cancer, for instance.
"This understanding is pivotal as it allows us to classify tumours based on their evolutionary trajectory rather than solely on individual gene mutations or expression patterns."
Researcher Prof Colin Cooper, from UEA鈥檚 Norwich Medical School, highlighted that while prostate cancer is responsible for a large proportion of all male cancer deaths, it is more commonly a disease men die with rather than from. This means that unnecessary treatment can often be avoided, sparing men from side-effects such as incontinence and impotence.
He added: 鈥淭his study is really important because until now, we thought that prostate cancer was just one type of disease. But it is only now, with advancements in artificial intelligence, that we have been able to show that there are actually two different subtypes at play.
鈥淲e hope that the findings will not only save lives through better diagnosis and tailored treatments in the future, but they may help researchers working in other cancer fields better understand other types of cancer too.鈥
Dr Naomi Elster, Director of Research at Prostate Cancer Research, said: 鈥淲e simply don鈥檛 know enough about what a prostate cancer diagnosis means at present 鈥 there are many men who have disease which is or may become aggressive and being able to treat aggressive disease more effectively is critical. But on the other side of the coin are the too many men who live with side effects of cancer treatment they may never have needed.
鈥淭hese results could be the beginning of us being able to take the same 鈥榙ivide and conquer鈥 approach to prostate cancer that has worked in other diseases, such as breast cancer.鈥
Professor Ros Eeles, Professor of Oncogenetics at The Institute of Cancer Research, London, and Honorary Consultant in Clinical Oncology and Cancer Genetics at The Royal Marsden NHS Foundation Trust, said: 鈥淭his study has utilised the enormous genomic dataset from The Pan Prostate Cancer Group 鈥 a powerhouse of information about prostate cancer from around the world. These results will hopefully lead to better treatments for patients, demonstrating the importance of data sharing and team science.鈥
The study - 鈥樷 is published online in the journal Cell Genomics.
]]>The EPSRC AI Hub for Causality in Healthcare AI with Real Data (CHAI) will develop new ways of unearthing important links in complex health data.
The hub will develop ways to use AI to enable the early prediction of debilitating diseases thanks to the 拢12m funding from the Engineering and Physical Sciences Research Council (EPSRC).
It is part of the nine centres announced as part of EPSRC鈥檚 拢80m UK-wide investment in applying AI to real world data and research.
CHAI aims to develop AI that can empower decision making tools to improve challenging tasks such as the early prediction, diagnosis and prevention of disease, and 鈥 crucially 鈥 to improve the safety of such technology in healthcare.
Researchers hope to apply this new technology to tackle key societal health challenges such as understanding infection, Alzheimer鈥檚, improving cancer treatments, social care, diabetes, and rehabilitation.
CHAI will be led by The University of Edinburgh鈥檚 Professor Sotirios Tsaftaris, Canon Medical/RAEng Chair in Healthcare AI.
Professor Tsaftaris said: 鈥淚'm delighted that the University of Edinburgh will be leading this world-leading consortium to develop next generation Causal AI. Causal AI holds tremendous promise for creating a new generation of AI solutions that are more robust, fair, safe, and transparent. Causal AI offers a step change in what AI can do for health with the proper safeguards. To fulfil this vision CHAI brings together an incredible team from across the UK (Imperial, 黑料网吃瓜爆料, UCL, Exeter, KCL), several affiliated researchers and domain experts, as well as more than 50 world-leading partner organisations to work together to co-create solutions thoroughly integrating ethical and societal aspects.
鈥淚 am extremely excited to lead this hub, particularly because of the strong people focus ensuring that we prepare the next generation of researchers in such cutting-edge AI methods.鈥
, who directs the University of 黑料网吃瓜爆料 part of the hub said: 鈥淚 am so excited to be a part of the new CHAI hub. The focus on causality aligns with key strengths at the University, and ensures that we can build AI for healthcare that is robust, fair, and directly applicable to decision support. This is a genuine opportunity for us to transform the role of AI in health.鈥
]]>Though methotrexate is the first-line drug to be given for Juvenile idiopathic arthritis (JIA), it is only effective or tolerated in half of the children and young people who receive it.
Those patients not helped by the drug have to wait longer to receive second line therapies, potentially prolonging the severe joint pain and other symptoms which often have a devastating impact on children and their families.
The study, published in the journal eBioMedicine, could facilitate more precise research into the identification of response predictors to methotrexate, such as biomarkers, and lead to better forecasting of likely outcomes following drug initiation.
It confirms that one in eight children and young people starting methotrexate will demonstrate improvements in inflammatory features of disease yet have some symptoms.
They also showed that in 16 per cent of children taking methotrexate, improvements in disease activity could be slower than in others over time.
Lead author said: 鈥淕iving methotrexate to children who it will not help wastes time, money and effort for healthcare services- as well as unnecessarily exposing them to potential side effects.
鈥淏ut now machine learning has opened the door made it possible to predicting which aspects of a child鈥檚 disease would be helped by the drug and so which children should start other therapies either alongside or instead of methotrexate straight away.
鈥淚n addition, this work shows how clinical trials are missing the mark in only looking at drug 鈥榬esponse鈥 or 鈥榥on-response鈥 for childhood-onset arthritis.
鈥淭his oversimplification could lead to a drug being labelled as 鈥榚ffective鈥 when key symptoms such as pain remain, or 鈥榠neffective鈥 where a significant improvement is seen in one aspect of this complex disease.鈥
The research is funded by the Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children鈥檚 Charity, Olivia鈥檚 Vision, and the National Institute for Health Research as part of the CLUSTER consortium.
The research team accessed data from four nationwide cohorts of children and young people who began their treatment before January 2018.
Juvenile arthritis disease activity score components (including how many swollen joints, a doctor鈥檚 perception of disease, a patient/parent report of wellbeing, results of a blood test for inflammation) were recorded at the start of treatment and over the following year.
They used machine learning identify clusters of patients with distinct disease patterns following methotrexate treatment, predict clusters; and compare clusters to existing treatment response measures.
From 657 children and young people verified in 1241 patients they identified Fast improvers (11%), Slow Improvers (16%), Improve-Relapse (7%), Persistent Disease (44%).
Two other clusters they called Persistent physician global assessment (8%) and Persistent parental global assessment (13%), were characterised by improvement in all activity score features except one.
Dr Shoop-Worrall added: 鈥淭he longer-term impact of this slower disease control needs further investigation. Our study also demonstrates the utility of machine learning methods to uncover clusters of children as a basis for stratified treatment decisions.
鈥淭his work builds on existing studies of methotrexate treatment response, confirming that response is not bivariate but can be highly variable across different features of disease within individuals.
鈥淎t the moment trials of methotrexate in JIA categorise patients into responders and non-responders.
鈥淭hat misclassification can compromise studies looking to identify predictors of response, such as biomarkers.鈥
The purpose of the consortium will be to provide Sellafield Ltd with technical support as it delivers its long-term objectives of safely inspecting and decommissioning their facilities using remote technologies.
Sellafield Ltd have made considerable progress with the deployment of robots to address challenges on its site. However, there are many challenges that remain, many of which cannot be solved using currently available commercial technologies.
The academic consortium will be led by Professor Barry Lennox and Dr Simon Watson at 黑料网吃瓜爆料 and supported by groups at The University of Bristol, led by Professor Tom Scott, and The University of Oxford, led by Professor Nick Hawes. Sellafield Ltd鈥檚 engagement with the academic consortium will be led by its Robotics and Manufacturing Lead, Dr Melissa Willis.
Melissa Willis, Robotics and Manufacturing Research Lead at Sellafield Ltd, added: 鈥We are excited by the opportunities that this consortium provides us with and are confident that their technical expertise will help us to deliver the benefits that robotics technology offers us on the Sellafield site.鈥
The consortium has considerable experience of working with Sellafield Ltd, having all been involved in the RAIN (Robotics and Artificial Intelligence for Nuclear) hub, and more recently 黑料网吃瓜爆料 has provided the academic leadership for the Robotics and AI Collaboration (RAICo) in Cumbria.
Experience of the consortium includes the design, development and deployment of mobile robots in a range of air, land and aquatic environments in the UK and overseas.
Working collaboratively with Sellafield Ltd, researchers at 黑料网吃瓜爆料 developed AVEXIS, which can be deployed into aquatic facilities with access ports as small as 150 mm and collect visual and radiometric data. The commercial version of AVEXIS was the first robot to be deployed into Sellafield鈥檚 Magnox Swarf Storage Silos and its use at Fukushima Daiichi has been explored.
The University of Oxford鈥檚 Robotics Institute (ORI) have developed a range of mapping and mission planning technologies that can be used by robots, such as Boston Dynamics鈥 Spot to autonomously monitor facilities and identify unexpected changes.
Using quadrotor and fixed wing vehicles, the University of Bristol have developed technology able to map radioactivity levels over large areas of land. The technology has been deployed successfully in the UK and overseas, with the image showing a radiation dose map generated over the Red Forest area of the Chornobyl Exclusion Zone, Ukraine, with the orange/red areas showing regions of elevated gamma dose rates.
]]>Viscount Camrose started his tour at Engineering Building A, home to the new international research centre CRADLE (Centre for Robotic Autonomy in Demanding and Long-lasting Environments), where he announced the countdown to the centre鈥檚 official opening in November.
The Minister was guided by Professor Barry Lennox, The University of 黑料网吃瓜爆料鈥檚 Centre for Robotics and AI Co-Director, where he learnt all about the interdisciplinary research going on in the centre, including a demonstration of a robot named Lyra, built to help transform nuclear infrastructure inspection.
Lyra was used to survey one of the radiologically contaminated ducts in Dounreay. It performed the equivalent of more than 400 air-fed suited entries into the site, equal to 2,250 man-hours. This capability reduced costs by an estimated 拢5m and it is predicted that similar surveys could save decommissioning costs by a further 拢500m in the future.
The Minister then took a tour of the Graphene Engineering Innovation Centre (GEIC), taking in its energy storage labs, printing lab facilities and construction materials testing facility, before making his way to ID 黑料网吃瓜爆料 and the location for the (TIC); a project which aims to link businesses to cutting-edge AI research and technologies to help enhance productivity.
John Holden, Associate Vice-President for Major Special Projects at 黑料网吃瓜爆料, said: 鈥淚 was delighted to welcome the minister to 黑料网吃瓜爆料 and to show him the leading-edge research and development activity we are undertaking in areas critical to the UK鈥檚 future economic growth and prosperity, including our pioneering work in AI and robotics.
鈥淔unding research and development in universities is critical to regional and national efforts to improve productivity across all industries, and the visit was an opportunity to highlight to the minister how we are accelerating the translation of our research base into industrial application through initiatives such as GEIC and the Turing Innovation Catalyst.
鈥淭he visit was also an opportunity to highlight the major opportunity that ID 黑料网吃瓜爆料 represents for the region and UK 鈥 our plan to transform eight hectares of the North Campus into a commercially-led innovation district will create a world-leading innovation ecosystem around the University and has the potential to create 10,000 high quality jobs in research and development intensive sectors linked to the University鈥檚 capabilities over the next 10-15 years.鈥
The Minister for AI and Intellectual Property, Viscount Camrose, added: 鈥淕reater 黑料网吃瓜爆料 has long been at the forefront of science and innovation in this country, from the first splitting of the atom to the invention of the first computer.
鈥淏y engaging closely with partners including 黑料网吃瓜爆料, businesses and local government, we can continue to grow our innovation economy across the country and level-up the UK.
鈥淚t was great to see first-hand some of the fantastic Government-backed research in 黑料网吃瓜爆料, such as the development of graphene applications at the GEIC, CRADLE鈥檚 cutting-edge innovations in robotics, as well as some of the projects underway through our 拢100m Innovation Accelerators programme such as the Turing Innovation Catalyst, the Centre for Digital Innovation and the Immersive Technologies Innovation Hub.鈥
The visit ended with a round-table discussion about the . Led by Innovate UK on behalf of the Department for Science, Innovation Technology (DSIT), the pilot programme is investing 拢100m in 26 transformative R&D projects to accelerate the growth of three high-potential innovation clusters 鈥 Greater 黑料网吃瓜爆料, Glasgow City Region and the West Midlands.
Leaders from three AI-related projects backed by the Innovation Accelerator 鈥 the Turing Innovation Catalyst, led by 黑料网吃瓜爆料, the Centre for Digital Innovation, led by 黑料网吃瓜爆料 Metropolitan University, and the MediaCity Immersive Technologies Innovation Hub, led by The Landing at MediaCityUK 鈥 attended the round-table. They were joined by Cllr Bev Craig, Leader of 黑料网吃瓜爆料 City Council and Greater 黑料网吃瓜爆料 lead for Economy, Business and International, and representatives from Greater 黑料网吃瓜爆料 Combined Authority (GMCA).
Participants discussed how to strengthen connections between these projects and maximise their value, and other national initiatives to support AI and related technologies.
Cllr Bev Craig, Leader of 黑料网吃瓜爆料 City Council and GMCA Lead for Economy and Business, said: 鈥淭oday鈥檚 visit provided a fantastic opportunity for the minister to learn more about the groundbreaking research and innovation happening right here in Greater 黑料网吃瓜爆料, and particularly at 黑料网吃瓜爆料.
鈥淚n recent years we have grown a reputation as a leading digital city-region, with AI as an important emerging sub-sector. As the impact of AI on our economy and society continues to grow, Greater 黑料网吃瓜爆料 is well-placed, with the potential to go even further.
鈥淲e also held a productive discussion about Greater 黑料网吃瓜爆料鈥檚 Innovation Accelerator programme and its AI-related projects. Through the Innovation Accelerator we are piloting a new model of R&D decision making that empowers local leaders to harness innovation in support of regional economic growth.鈥
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