̽��ֱ�� of Cambridge - Zoe Kourtzi

AI can be good for our health and wellbeing

cjb250 — Mon, 07 Apr 2025 08:00:08 +0000

Cambridge researchers are looking at ways that AI can transform everything from drug discovery to Alzheimer's diagnoses to GP consultations.

Minister for AI and Digital Government visits Cambridge to tour the DAWN supercomputer

Anonymous — Mon, 13 Jan 2025 16:34:50 +0000

Feryal Clark MP was welcomed to the ̽��ֱ��’s DAWN supercomputer facility, located on the ̽��ֱ��’s West Cambridge Innovation District, by Pro-Vice-Chancellor for Research, Professor John Aston, and Dr Paul Calleja, Director of Research Computing Services at the ̽��ֱ��.

Together they toured the DAWN supercomputer and met with representatives from academia and industry partners who have ambitious plans for AI and supercomputing in Cambridge. ̽��ֱ��visit comes as the Government opens a UK-wide call for early access to the new AI Research Resource service, of which DAWN is part of.

Now up and running in its state-of-the-art Data Centre in Cambridge, DAWN is currently the most powerful AI supercomputer in the UK, with more than a thousand top-end Intel graphics processing units (GPUs) operating inside its server stacks. ̽��ֱ��supercomputer’s bespoke innovations in hardware and software result from a long-term co-design partnership between the Cambridge Open Zettascale Lab, directed by Dr Paul Calleja, and global tech leaders Intel and Dell Technologies, with support from the UK Atomic Energy Authority (UKAEA), StackHPC and UK Research & Innovation.

Our world-leading researchers are exploring how AI can benefit society.

̽��ֱ��Vice-Chancellor, Professor Deborah Prentice, also welcomed the Minister to the Wolfson Brain Imaging Centre on the Cambridge Biomedical Campus, where they were able to learn about the impact of DAWN and AI on patients, with a demonstration of the advances in healthcare.

Feryal Clark MP later toured the ̽��ֱ��’s latest brain imaging scanner and heard from leading ̽��ֱ�� researchers who are utilising DAWN supercomputing capabilities and AI to improve patient outcomes, and develop new and innovative treatments.

̽��ֱ��Minister moved on to meet with Professor Zoe Kourtzi, whose team are working on improving the early diagnosis of Alzheimer's, for which AI can help develop tools by combining diverse data sources that provider a richer picture of a patient’s brain health. Professor James Brenton also presented on his work developing a comprehensive clinical decision-making support platform that integrates and refines cancer patient data from multiple sources into a single, much more manageable tool. Feryal Clark MP further heard from researcher Bill McGough, who is working on a project to develop an AI tool to detect renal cancers in non-contrast and low-dose CT, to enable kidney screening in the UK.

̽��ֱ�� ̽��ֱ�� of Cambridge is home to world-leading researchers in AI, to students enthusiastic about the potential of AI, and to an innovation ecosystem that is successfully translating this research into innovative new start-ups and creating jobs. ̽��ֱ�� ̽��ֱ��’s flagship AI@Cam is harnessing the ̽��ֱ��'s interdisciplinary research to drive a new wave of AI innovation that delivers public value.

̽��ֱ��Minister for AI and Digital Government, Feryal Clark MP, visited the ̽��ֱ�� of Cambridge on the day the Government announced their new AI Action Plan.

Lloyd Mann / ̽��ֱ�� of Cambridge

Left to right: Nicola Ayton, Deputy Chief Executive of Cambridge ̽��ֱ�� Hospitals (CUH), Feryal Clark MP, Minister for AI and Digital Government, Vice-Chancellor of Cambridge ̽��ֱ��, Professor Deborah Prentice

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Licence type:

Attribution

Artificial intelligence outperforms clinical tests at predicting progress of Alzheimer’s disease

cjb250 — Fri, 12 Jul 2024 22:30:52 +0000

̽��ֱ��team say this new approach could reduce the need for invasive and costly diagnostic tests while improving treatment outcomes early when interventions such as lifestyle changes or new medicines may have a chance to work best.

Dementia poses a significant global healthcare challenge, affecting over 55 million people worldwide at an estimated annual cost of $820 billion. ̽��ֱ��number of cases is expected to almost treble over the next 50 years.

̽��ֱ��main cause of dementia is Alzheimer’s disease, which accounts for 60-80% of cases. Early detection is crucial as this is when treatments are likely to be most effective, yet early dementia diagnosis and prognosis may not be accurate without the use of invasive or expensive tests such as positron emission tomography (PET) scans or lumbar puncture, which are not available in all memory clinics. As a result, up to a third of patients may be misdiagnosed and others diagnosed too late for treatment to be effective.

A team led by scientists from the Department of Psychology at the ̽��ֱ�� of Cambridge has developed a machine learning model able to predict whether and how fast an individual with mild memory and thinking problems will progress to developing Alzheimer’s disease. In research published today in eClinical Medicine, they show that it is more accurate than current clinical diagnostic tools.

To build their model, the researchers used routinely-collected, non-invasive, and low-cost patient data – cognitive tests and structural MRI scans showing grey matter atrophy – from over 400 individuals who were part of a research cohort in the USA.

They then tested the model using real-world patient data from a further 600 participants from the US cohort and – importantly – longitudinal data from 900 people from memory clinics in the UK and Singapore.

̽��ֱ��algorithm was able to distinguish between people with stable mild cognitive impairment and those who progressed to Alzheimer’s disease within a three-year period. It was able to correctly identify individuals who went on to develop Alzheimer’s in 82% of cases and correctly identify those who didn’t in 81% of cases from cognitive tests and an MRI scan alone.

̽��ֱ��algorithm was around three times more accurate at predicting the progression to Alzheimer’s than the current standard of care; that is, standard clinical markers (such as grey matter atrophy or cognitive scores) or clinical diagnosis. This shows that the model could significantly reduce misdiagnosis.

̽��ֱ��model also allowed the researchers to stratify people with Alzheimer’s disease using data from each person’s first visit at the memory clinic into three groups: those whose symptoms would remain stable (around 50% of participants), those who would progress to Alzheimer’s slowly (around 35%) and those who would progress more rapidly (the remaining 15%). These predictions were validated when looking at follow-up data over 6 years. This is important as it could help identify those people at an early enough stage that they may benefit from new treatments, while also identifying those people who need close monitoring as their condition is likely to deteriorate rapidly.

Importantly, those 50% of people who have symptoms such as memory loss but remain stable, would be better directed to a different clinical pathway as their symptoms may be due to other causes rather than dementia, such as anxiety or depression.

Senior author Professor Zoe Kourtzi from the Department of Psychology at the ̽��ֱ�� of Cambridge said: “We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow.

“This has the potential to significantly improve patient wellbeing, showing us which people need closest care, while removing the anxiety for those patients we predict will remain stable. At a time of intense pressure on healthcare resources, this will also help remove the need for unnecessary invasive and costly diagnostic tests.”

While the researchers tested the algorithm on data from a research cohort, it was validated using independent data that included almost 900 individuals who attended memory clinics in the UK and Singapore. In the UK, patients were recruited through the Quantiative MRI in NHS Memory Clinics Study (QMIN-MC) led by study co-author Dr Timothy Rittman at Cambridge ̽��ֱ�� Hospitals NHS Trust and Cambridgeshire and Peterborough NHS Foundation Trusts (CPFT).

̽��ֱ��researchers say this shows it should be applicable in a real-world patient, clinical setting.

Dr Ben Underwood, Honorary Consultant Psychiatrist at CPFT and assistant professor at the Department of Psychiatry, ̽��ֱ�� of Cambridge, said: “Memory problems are common as we get older. In clinic I see how uncertainty about whether these might be the first signs of dementia can cause a lot of worry for people and their families, as well as being frustrating for doctors who would much prefer to give definitive answers. ̽��ֱ��fact that we might be able to reduce this uncertainty with information we already have is exciting and is likely to become even more important as new treatments emerge.”

Professor Kourtzi said: “AI models are only as good as the data they are trained on. To make sure ours has the potential to be adopted in a healthcare setting, we trained and tested it on routinely-collected data not just from research cohorts, but from patients in actual memory clinics. This shows it will be generalisable to a real-world setting.”

̽��ֱ��team now hope to extend their model to other forms of dementia, such as vascular dementia and frontotemporal dementia, and using different types of data, such as markers from blood tests.

Professor Kourtzi added: “If we’re going to tackle the growing health challenge presented by dementia, we will need better tools for identifying and intervening at the earliest possible stage. Our vision is to scale up our AI tool to help clinicians assign the right person at the right time to the right diagnostic and treatment pathway. Our tool can help match the right patients to clinical trials, accelerating new drug discovery for disease modifying treatments.”

This work was in collaboration with a cross-disciplinary team including Professor Peter Tino at the ̽��ֱ�� of Birmingham and Professor Christopher Chen at the National ̽��ֱ�� of Singapore. It was funded by Wellcome, the Royal Society, Alzheimer’s Research UK, the Alzheimer’s Drug Discovery Foundation Diagnostics Accelerator, the Alan Turing Institute, and the National Institute for Health and Care Research Cambridge Biomedical Research Centre.

Reference
Lee, LY & Vaghari, D et al. Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings. eClinMed; 12 July 2024; DOI: 10.1016/j.eclinm.2024.102725

Cambridge scientists have developed an artificially-intelligent tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer’s disease.

We’ve created a tool which is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s

Zoe Kourtzi

Yuichiro Chino (Getty Images)

Brain on molecular structure, circuitry, and programming code background

Yes

Using AI to tackle society's biggest challenges

cjb250 — Mon, 05 Feb 2024 08:00:28 +0000

̽��ֱ��winners of a new prize supporting ambitious ideas for how artificial intelligence can address critical societal issues are announced today, with projects spanning fertility, climate change, language and communication challenges, mental health, and how local councils deploy AI.

Tuning into brainwave rhythms speeds up learning in adults

fpjl2 — Tue, 31 Jan 2023 14:28:09 +0000

̽��ֱ��first study to show that delivering information at the natural tempo of our neural pulses accelerates our ability to learn.

AI could detect dementia years before symptoms appear

cjb250 — Thu, 12 Aug 2021 08:44:50 +0000

Artificial intelligence could spot the early signs of dementia from a simple brain scan long before major symptoms appear – and in some cases before any symptoms appear – say Cambridge researchers.

Cambridge ̽��ֱ�� and Nanyang Technological ̽��ֱ��, Singapore establish new research centre to support lifelong learning

Anonymous — Tue, 06 Oct 2020 14:50:57 +0000

̽��ֱ��Centre for Lifelong Learning and Individualised Cognition (CLIC) is a collaboration between the ̽��ֱ�� of Cambridge and the Nanyang Technological ̽��ֱ��, Singapore (NTU Singapore), and is funded by Singapore’s National Research Foundation.

Cultivating new skills is a lifelong process that requires cognitive flexibility, yet there is currently a gap in evidence-based training programmes that can effectively support and promote this way of learning throughout people’s lives.

Cognitive flexibility goes far beyond conventional IQ; it is the essential capacity for responding to the fluctuating events of the modern world. It underlies adaptive coping to change, and also the generation of innovative, creative thinking.

Trevor Robbins, Professor of Cognitive Neuroscience Psychology in the ̽��ֱ�� of Cambridge’s Department of Psychology and a senior academic advisor to the programme, said: "Understanding the psychological basis of cognitive flexibility and its basis in the brain will have enormous societal benefits, with educational, as well as clinical, impact.”

He added: “This novel and original collaborative programme by two leading Universities will enhance the science of learning by innovative interventions and methods, for training cognitive flexibility over the life span."

̽��ֱ��research programme will be led by Zoe Kourtzi, Professor of Experimental Psychology in Cambridge’s Department of Psychology. Involving researchers in psychology, neuroscience, linguistics and education, CLIC will explore cross-disciplinary ways to develop innovative research in the science of learning. ̽��ֱ��ultimate goal is to translate these research findings into an integrated model of learning that can be applied in the real world, improving cognitive flexibility across the life span.

Research will focus on four life stages - early years, adolescence, young adults and middle age - when flexible behaviour is critical for coping with changing circumstances. During these periods the brain undergoes neural changes such as early maturation, restructuring or resilience to decline, presenting important opportunities for intervention.

NTU Senior Vice President (Research), Professor Lam Khin Yong said: “ ̽��ֱ��cross-disciplinary collaboration between researchers from NTU Singapore and Cambridge ̽��ֱ�� is expected to have wide-ranging impact on workers, as technology and globalisation change the nature of labour markets worldwide.”

He added: “ ̽��ֱ��ability to develop and master new skills at the workplace is becoming increasingly pressing globally. Singapore’s nationwide SkillsFuture programme, for example, gives opportunities for people to develop their fullest potential throughout life. Yet, we know that differences in individual cognitive functions can affect learning and performance. This is where research in the Science of Learning can play a key role in enhancing educational outcomes and practice. ̽��ֱ��new Centre will support the country’s drive in helping the workforce prepare for the digital economy, as businesses turn to automation.”

Annabel Chen, Co-Director of CLIC and Professor of Psychology and Director for the Centre for Research and Development in Learning (CRADLE) at NTU, Singapore, said: “This is an exciting development for research in the Science of Learning. We have been working closely with colleagues from Cambridge, and tapping into expertise across NTU, including the College of Humanities, Arts and Social Sciences, Nanyang Business School, National Institute of Education, Lee Kong Chian School of Medicine and College of Engineering to develop the CLIC programme.”

She added: “This development complements the Science of Learning Initiative in the Centre of Research and Development in Learning (CRADLE), launched by NTU in 2015. With this multidisciplinary effort and input from the Ministry of Education and SkillsFuture Singapore, we believe our programme will be able to provide insights and translatable solutions for the Future of Learning and Economy in Singapore and beyond.”

̽��ֱ��collaboration was brought together through the presence of the ̽��ֱ�� of Cambridge’s first overseas research centre in Singapore, the Centre for Advanced Research and Education in Singapore Ltd (CARES). CARES was established in 2013 under the Campus for Research Excellence and Technological Enterprise (CREATE) – a collection of 15 joint research programmes between local universities and top overseas institutions funded by Singapore’s National Research Foundation (NRF). ̽��ֱ��Centre hosts several research programmes, most of which involve NTU and focus on the decarbonisation of Singapore’s chemical industry.

̽��ֱ��new programme on the science of learning is a novel direction for CARES and CREATE, bringing together expertise from Cambridge and Singapore to investigate new ways of helping people prepare and adapt to the rapidly changing workplace.

A new research centre focused on improving support for lifelong learning and cognitive agility opened on 1 October 2020 in Singapore.

̽��ֱ��programme will enhance the science of learning by innovative interventions and methods, for training cognitive flexibility over the life span

Trevor Robbins

Jess Bailey on Unsplash

Coloured pencils

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Licence type:

Attribution-Noncommerical

Spotlight on children

lw355 — Thu, 01 Nov 2018 09:00:00 +0000

̽��ֱ��importance of supporting children to grow into happy, healthy and inquiring adults is abundantly clear. Physical and mental wellbeing in children is a foundation for a healthy and productive life.

And yet we live in a world where one in four of us will experience the isolating and traumatic effects of mental health disorders, three-quarters of which begin before the age of 18; children are still held back throughout life as a result of low levels of literacy and numeracy; and up to one billion young people worldwide are likely to be victims of violence this year.

Our researchers are studying all aspects of children, helping to understand how a child’s early experiences can shape their lifelong development. Today we launch both a Spotlight on children and the latest issue of the ̽��ֱ��’s Research Horizons magazine to showcase examples of this research.

We address some of the big questions, such as what are the origins of mental health and why are teenagers so vulnerable to mental disorders? We take a life course and multidisciplinary approach to the problem: from a child’s genes and clinical development in the womb, through the neuroscience and psychology of learning disorders, to psychiatric approaches aimed at understanding why some children are more at risk of developing mental health problems in later life and why some are resilient.

“We marvel at the brain’s complexity,” says Professor David Rowitch, who leads the Department of Paediatrics. “Across the ̽��ֱ��, no stone is left unturned in our attempts to better understand how to ensure healthy brain development and learning, as well as neurological and mental health, throughout life. We recognise how profoundly quality of life is affected. As this Spotlight focus will show, neurological and mental health has high priority both in basic research and clinical medicine, and in government policy.”

We also ask about life experiences. Tragically some children and their mothers are exposed to violence and drugs before they are even born, or grow up in communities entrenched in crime, and where healthcare systems are failing. Yet we know little about the effects of adverse environments – on people and on the stability of societies in which they become citizens. A pilot study to understand what it means to be a child of the city today is following 1,200 children in eight cities in all major regions of the Global south.

Professor Manuel Eisner, from the Institute of Criminology and who leads the study, explains: “By comparing a new generation from each city, we can build a scientific backbone for interventions to prevent violence against children as well as against their mothers, and support stakeholders to take wellbeing initiatives that work in different global contexts.”

Education features prominently in our research. In India, for instance, researchers are working with local partners to ask whether low learning outcomes could be a by-product of an Indian school system in which the language that children are taught in school often differs to the language spoken at home. And in Cambridge, where the ̽��ֱ�� of Cambridge Primary School is sponsored by the ̽��ֱ�� to provide education for the local community in North West Cambridge, we examine how the School places research at its heart – in both informing education practice and in furthering research at Cambridge’s Faculty of Education and elsewhere.

What about the role of parents? It’s clear that our mothers, fathers and families affect our lives and the people we become, but are we focusing too much on the ‘skill’ of parenting and losing sight of things that matter more – like how we talk to and play with children? Researchers are piecing together the complex jigsaw that involves families, language, play, and physical and psychological health to better understand what gives a child the best chance in life.

“ ̽��ֱ��modern digital age challenges us to cope with rapidly changing settings at home, school, work and leisure,” says Professor Zoe Kourtzi from the Department of Psychology. “Our propensity to learn and rapidly adapt is thus central to 21st-century life. These challenges are particularly marked in the early and later periods of life, when young children are preparing or progressing through years of intensive education and older adults are facing major changes to their health and social circumstances.

“Research at Cambridge aims to understand how learning supports flexible behaviour and resilience to the new challenges that individuals face across the life course. Using interdisciplinary methodologies, we aim to enhance basic understanding of the mechanisms of lifelong learning, and transform this knowledge into innovative personalised interventions that will promote public wellbeing through applications in education, social care, public health and policy.”

Some of our research is having unexpected effects – such as a book of ‘lost words’ that encourages children to love and protect the natural world. Thanks to crowdfunding campaigns, the book is appearing in primary schools across the UK – an outcome that has surprised and moved its creators, who hope the book will help to bridge social gaps in the uneven distribution of access to nature.

Underpinning much of the Spotlight is the idea so eloquently put by the 19th-century American social reformer Frederick Douglass: “It is easier to build strong children than to repair broken men”.

Professor Manuel Eisner (Institute of Criminology), Professor Zoe Kourtzi (Department of Psychology) and Professor David Rowitch (Department of Paediatrics) are editorial advisors for the 'Spotlight on children' issue of Research Horizons magazine (see inset image), which is available as a PDF and on Issuu

Welcome to our new ‘Spotlight on children’, a focus on research taking place at the ̽��ֱ�� of Cambridge relating to children and childhood – from health to education, language to literacy, parents to playtime, risk to resilience.

It is easier to build strong children than to repair broken men

Frederick Douglass, 19th-century American social reformer

̽��ֱ�� of Cambridge Primary School

Yes