Computing technologies for healthcare
The School pioneers healthcare technologies that target applications in computational biology, intelligent social agents, decision support tools, brain computer interfaces and health monitoring. Statistical machine learning approaches explain cancer and virus evolution, provide decision support based on Electronic Health Records and develop intelligent agents that sense human neurophysiology and provide support in mental and psychiatric disorders including dementia, autism and depression. The School has more than 30 years’ experience in information retrieval that relates to privacy issues and fair-representations in sensitive data. The School is also involved in building the next generation of quantum imaging technology for monitoring of Wellbeing and disease.
There is a strong culture of inter-disciplinary research and training via several links that include Glasgow Polyomics, Institute of Cancer Sciences, MRC Centre for Virus Research, Glasgow Precision Oncology Laboratory, Robertson Centre for Biostatistics, the Institute of Neuroscience and Psychology, the Adam Smith Business School, the School of Critical Studies, the School of Engineering, the Scottish Graduate School of the Social Sciences and the School of Physics and Astronomy.
Theme Lead: Dr Stephen Lindsay
Current Projects
The Social AI CDT 2019-2027. EPSRC
Prof Alessandro Vinciarelli, Prof Iadh Ounis, Dr Mary-Ellen Foster
The Social AI CDT, based at the University of Glasgow, is a collaboration between the School of Computing Science, the School of Psychology & Neuroscience, the Adam Smith Business School, the School of Critical Studies, the School of Engineering, the Scottish Graduate School of the Social Sciences and 17 industrial partners to 1) outline principles and laws that govern social interactions between human and artificial agents – both embodied and virtual – at the level of cognitive, behavioural and physiological phenomena 2) to improve the impact of artificial agents through their integration into wider and more complex technological systems and infrastructures 3) to develop technological approaches – informed by the principles and laws outlined in 1 – that allow artificial agents to act as believable and effective partners in social interactions involving human users and 4)to investigate the human response to socially intelligent artificial agents in everyday life.
Beyond One Solution in Combinatorial Optimisation 2021-2026. EPSRC
Dr. Kitty Meeks (PI), Dr. Jessica Enright, Dr. Craig Anderson, Dr. Bhautesh Jani
A £1.36 million EPSRC fellowship which will develop new methods for understanding the space of all "good" solutions to optimisation problems - such as clustering - rather than searching for a single "best" solution, and apply these techniques to address challenges in digital health. Specific applications include treatments for heart failure, diagnosis of endometriosis, targeted cancer screening, and the identification of optimal interventions for infectious disease control.
KidneyAlgo: New Algorithms for UK and International Kidney Exchange 2023-2025. EPSRC
Prof David Manlove
This collaborative project with Durham University involves developing new algorithms and software for the UK Living Kidney Sharing Scheme (UKLKSS) and for other kidney exchange programmes (KEPs) around Europe. The new algorithms will allow for more complex exchange structures, larger pools and different optimality objectives within the UKLKSS. For international kidney exchange programmes that involve collaboration between multiple countries, the algorithms will ensure fairness and stability, incentivising countries to participate in a shared KEP.
Privacy-Preserved Human Motion Analysis for Healthcare Applications 2022-2025. EPSRC
Dr. Fani Deligianni
A new investigator award, which will develop artificial intelligence algorithms for human motion analysis in healthcare applications that preserve users' privacy
Quantum Imaging for Monitoring of Wellbeing & Disease in Communities 2020-2025. EPSRC
Prof. Roderick Murray-Smith (Co-I)
A multi-million project on how quantum imaging will enable remote detection and monitoring of parameters such as gait, macro and micro-movements, blood flow, heart rate and potentially even brain function. When combined with data-driven models, will allow to both monitor health and the onset of non-communicable diseases (NCDs) but also recovery from NCDs or surgery with personalised and continuously updated re-habilitation programmes.
Safe Information Extraction from Patient Histories. 2023-2025. EPSRC
Dr. Graham McDonald, Dr. Jake Lever and Prof. Iadh Ounis
A New Horizons project to develop methods for extracting information from patient records while maintaining patient privacy. Information in the free text of medical records can be key to important medical discoveries but high-quality annotated text is needed for effective information extraction. This project will research the use of synthetic medical records to create text annotations which don't risk leaking sensitive information.
Digitalisation of livestock data to improve veterinary public health 2021-2024. NordForsk
Dr. Jessica Enright
The DigiVet project will study how livestock data is currently used across the partner nations, and how technology, training, and regulatory frameworks might provide societal benefit by improving the public-interest uses of these data.
Personalised Acceptance and Commitment Therapy (PACT) for Parkinson's Disease 2023-2024. ParkinsonsUK
Dr Siomone Stumpf
Living with Parkinson’s disease presents daily challenges, which can affect a person’s wellbeing. Face-to-face talking therapies are effective at improving wellbeing but can be time-consuming and difficult to access. The COVID-19 pandemic has reduced access to face-to-face support and expanded our digital world. Digital applications on smartphones and tablets are an effective way of delivering psychological support. The aim of this study is to develop and test a digital application which provides brief daily support for psychological wellbeing based on the talking therapy Acceptance and Commitment Therapy (ACT)
Pancreatic cancer AI for genomics and personalized Medicine. 2021-2024. Horizon 2020
Dr Ke Yuan
PANCAIM will combine genomics and imaging phenomics using AI to generate breakthrough knowledge to increase understanding of PDAC biology and patient stratification. It will develop trusted impactful AI applications for regular clinical use to help clinical decision-makers to give the right treatment to the right patients at the right time, and at the right cost and improve treatment outcomes of PDAC patients.
Multilayer Algorithmics to Leverage Graph Structure (MultilayerALGS) 2020-2023. EPSRC
Dr. Kitty Meeks, Dr. Jessica Enright, Prof Duncan Lee, Dr. Mark Wong, Dr. Heng Guo (University of Edinburgh)
A broad project about novel algorithmic techniques to handle network datasets involving qualitatively different types of edges (for example, physical and online contact in a social network) involves two application case studies related to healthcare: finding optimal epidemiological interventions when a disease spreads in a multi-layer networks, and identifying spatial patterns in disease risk for non-communicable diseases.
Using AI-Enhanced Social Robots to Improve Children's Healthcare Experiences 2020-2023. ESRC/SSHRC
Dr Mary-Ellen Foster
In this project, we aim to address this limitation by developing and evaluating a clinically relevant and responsive AI-enhanced social robot. We believe that interaction with a robust, adaptive, socially intelligent robot can effectively distract children during painful clinical procedures, thereby reducing pain and distress.
Academic Staff
Dr. Christos Anagnostopoulos, (Pervasive and Distributed Intelligence)
Dr. Matthew Barr, (Video games, well-being and mental health)
Prof. Stephen Brewster, (Human Computer Interactions technologies for mental disorders)
Dr. Kevin Bryson, (Bioinformatics and histopathology image analysis)
Dr. Mathieu Chollet, (Virtual Social Interactions)
Dr Hang Dai, (Computer vision and meidical imaging)
Dr. Jeff Dalton, AI Turing Fellow and former member of Google Health, (NLP, Deep Learning)
Dr. Fani Deligianni, (Decision support systems, analysis of neurophysiological data)
Dr. Xianghua Ding, (Patient-Provider Communication, Co-Production in Healthcare, and Health Tracking Technologies)
Dr. Jessica Enright, (Graph theory in epidemiology research)
Dr. Mary Ellen Foster, (Building artificial characters that interact naturally with people)
Dr Ali Gooya, (Computer vision and medical imaging)
Dr Edmond Ho, (Analyzing human data captured from visual sensors)
Dr Bjorn Jensen, (Biomedical imaging)
Dr. Jake Lever, (Information Extraction and Retrieval in Biomedical Applications)
Dr Emma Li, (Human-robot partnerships for health and social care)
Dr. Stephen Lindsay, (Digital healthcare and co-design)
Dr. Craig MacDonald, (Information Retrieval)
Dr. Marwa Mahmoud, (Multimodal behaviour analytics)
Prof. David Manlove, (Matching problems in the field of algorithms and complexity)
Dr. Zaiqiao Meng, (Biomedical knowledge graph and natural language processing)
Dr. Nikos Ntarmos, (Distributed (Big) data management)
Prof. Iadh Ounis, (Information Retrieval)
Dr. William Pettersson, (Complexity theory, Theoretical efficiency of an algorithm)
Dr. Kitty Meeks, (Graph theory in epidemiology research, clustering algorithms)
Dr. Lito Michala (Internet of Things)
Prof. Roderick Murray-Smith, (Inference, Dynamics and Interaction)
Dr. Jose Cano Reyes, (Computer Architecture, Edge Computing, Deep Learning)
Dr. Simon Rogers (Bioinformatics)
Dr. Simone Stumpf, (Responsible & Interactive Artificial Intelligence)
Prof. Alessandro Vinciarelli, (Computational Social Intelligence)
Dr John Williamson, (Human Computer Interfaces in healthcare applications)
Dr. Ke Yuan (Bioinformatics and cancer research)
Research Students
Asking questions about medical images. 2020-2024. Canon Medical Systems
Maciej Pajak, Dr. Fani Deligianni, Dr. Jeff Dalton
This project focuses on a range of methodological approaches in computer vision and natural language processing, which collectively support answering questions about 2D and 3D radiology images.
PhD Scholarship on Applying machine learning models to genome data to understand the evolution of drug resistance from virus to cancer evolution. 2020-2024. MRC Precision Medicine DTP
Dr. Ke Yuan.
PhD Scholarship on A Network Clustering Approach to Endometriosis Diagnosis. 2019-2023. MRC Precision Medicine DTP.
Dr. Kitty Meeks, Dr Craig Anderson
EngD project on multi-modal and self-supervised machine learning for medical image analysis. 2018-2021. Canon Medical Research
Dr. Bjorn Jensen
PhD Placement Mobility grant on ‘Endoscopic Surgery Image Enhancement’ 2020-2021. Newton Bhabha Fund
Dr. Jose Cano Reyes
This project aims to design hardware architectures to remove unwanted distortions in the input pixels due to surgical smoke or fog particles for real-time operations.
Past Projects
Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics
Prof. Roderick Murray-Smith, Dr. Craig Macdonald, Dr. Nikos Darmos, Prof. Iadh Iounis, Dr. Ke Yuan, Dr. Simon Rogers, Dr. Christos Anagnostopoulos, Dr. Bjorn Jensen, Dr. John Williamson
A multi-million project on ‘Closed-loop Data Science’ applied in several areas including personalisation of hearing aids and analysis of cancer data.
TREC Precision Medicine campaign 2020-2022.UFMG (Brazil),
Dr Craig Macdonald and Prof. Iadh Ounis
Developing search technologies for precision medicine and biomedical text. It come 2nd among 25 groups worldwide in the TREC Precision Medicine campaign in November (NIST, USA). The developed system was also one of the best performing among 50 participating groups in the TREC COVID campaign to automatically distil information from published articles as the pandemic progressed.
African COVID-19 preparedness (AFRICO19) 2020-2022. The Wellcome Trust
Dr. Ke Yuan (Co-I)
This project will enhance capacity to understand SARS-CoV-2/hCoV-19 infection in three regions of Africa (Kenya, The Gambia and Uganda) and globally.
UK Living Kidney Sharing Scheme 2016-2021. CA15210 - European Network for Collaboration on Kidney Exchange Programmes, European Cooperation in Science and Technology (COST)
Prof. David Manlove Dr. William Pettersson
Over 1200 kidney transplants identified by the algorithms developed at Glasgow that match patients and donors for the UK Living Kidney Sharing Scheme have proceeded to surgery. This is estimated to have saved the NHS around £90M over the period 2008-2030, taking into account the cost of the surgery versus the savings made by releasing a patient from long-term dialysis. Read more in these two articles: ‘How Operational Research Helps Kidney Patients in the UK’ and ‘Algorithms for Kidney Donation’
iCaird - the Industrial Centre for Artificial Intelligence Research in Digital Diagnostics. 2018 – 2021. Innovate UK
Prof. Rod Murray-Smith, Prof. Muffy Calder, Dr. Bjorn Sand Jensen and Dr. John Williamson
The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics was announced on the 6th of November 2018 as one of five successful bids to the UK Governments UKRI Industrial Strategy Challenge Fund (ISCF). It brings together a pan-Scotland collaboration of 15 founding partners from across industry, the NHS, and academia; including four current actively engaged SMEs. Industry leadership is provided by Canon Medical Research Europe (radiology) and Royal Philips (digital pathology). iCAIRD was awarded £10m in ISCF funding by Innovate UK, while partner companies Canon Medical Research Europe Ltd, Royal Philips and SMEs are collectively providing £6M of additional supportive funding. Today iCAIRD has more than 30 active partner companies, with over 30 current research projects across radiology and pathology
A Robot Training Buddy for Adults with ASD 2017-2021. EPSRC
Prof. Alessandro Vinciarelli and Dr. Mary Ellen Foster
This project promotes collaboration with the Scottish Autism Centre and it aims to teach social skills to autistic adults via robots.
Funded by EPSRC.
A high-content platform for cellular mechanobiology in cancer research. 2018-2021. CRUK
Dr Bjorn Jensen
The project aims to develop technological solutions of handling wearable data based on deep learning to address ethical and data privacy considerations of patients and their social cycle.
Human Motion Analysis – Agency, Negotiation and Legibility in Data Handling. 2020-2021. Human Data Interaction EPSRC Network
Dr. Fani Deligianni
Fast multi-shot epidemic interventions for post lockdown Covid-19 mitigation: Open-loop mitigation strategies, 2020. EPSRC funded project, EP/V018450/1.
Prof. Rod Murray-Smith
The objective of this project is to design and validate new exit-strategies from the current lockdown policy that actively suppress COVID-19, while allowing significant economic activity. Currently proposed exit-strategies suggest that intermittent lockdowns, in addition to contact tracing, masking, and other measures, may be necessary until an effective vaccine is found. Our suggestion is to develop periodic open-loop lockdown strategies over short timescales. Such policies will help suppressing the virus and allow predictable periodic periods of lockdown, thereby facilitating economic activity. The policies will be validated on advanced, realistic epidemiological mathematical models and data, and will be developed for national and international compartmental scenario
Technology Enabled Mental Health for Young People, 2016-2020.H2020 International Training Network
Prof. Steven Brewster
The network aims to design, develop and evaluate novel technologies to enable mental health services that are effective, affordable and accessible for young people.
Royal Society of Edinburgh/Scottish Enterprise Entrepreneurial Fellowship CH12 on Clydescope Health, 2018-2019
Dr Anna Lito Michala
This project focused on developing an automated mix and infusion system that monitored hypoglycaemia, prepared the glucagon and injected just in time to avoid loss of consciousness. The IoT device was edge processing information locally and only connected to a smartphone app to securely inform careers if intervention was required and alarm patients to take further action.
SAM: Automated Attachment Analysis Using the School Attachment Monitor, 2015-2018. EPSRC
Prof. Steven Brewster, and Prof Alessandro Vinciarelli
Analysis of attachment patterns in school age children with collaboration with the Adverse Childhood Experiences Centre.
MoreGrasp - 2015-2018. EC Horizon2020 project
Prof. Roderick Murray-Smith
Final Demo video. The aim of the MoreGrasp project is to develop a non-invasive, multi-adaptive, multimodal user interface including a brain-computer interface (BCI) for intuitive control of a semi-autonomous motor and sensory grasp neuroprosthesis supporting individuals with high spinal cord injury in everyday activities.
How to join
Funded PhD Opportunities on healthcare applications are provided via the following main routes:
Visit University of Glasgow vacancies for job opportunities.
Upcoming events
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Past events
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