Dr Weizi (Vicky) Li
Associate Professor of Informatics and Digital Health
Deputy Director of Informatics Research Centre
Programme Director of MSc Digital and Technology Solutions
Director of EPSRC Future Blood Testing for Inclusive Monitoring and Personalised Analytics Network+
Impact Lead of BISA Research Division
- Artificial Intelligence and machine learning,
- Information Systems,
- Digital Health,
- Advanced Analytics,
- Finance Technology,
- Decision Support System,
- Digital Leadership and Strategy
With a background in informatics, Dr Li is an interdisciplinary researcher focusing on solving challenges in healthcare using digital technology that combines AI, machine learning, information systems, medical science and social science.
Dr. Weizi (Vicky) Li is Associate Professor in Informatics and Digital Health, Deputy Director in Informatics Research Centre, Henley Business School, University of Reading. Her research focuses on digital health, information systems, artificial intelligence and machine learning applications. She is also a Fellow of the Chartered Institute of IT (FBCS).
Her research impact of improving healthcare quality and efficiency using the digital platform is recognised as one of the winners of O2RB Excellence in Impact Awards in 2018, supported by University of Oxford Economic Social Research Council Impact Acceleration Account. Her research with the NHS on “Applications and Implications of Machine Learning: Understanding and Predicting Healthcare Resource Usage and Patient Risk for Improved Population Engagement” was awarded the Economic Social Research Council grant in 2018. And her project of using machine learning to reduce appointment non-attendance in collaboration with the Royal Berkshire NHS Foundation Trust was awarded the Research Engagement and Impact Award in 2020.
Her other research projects are funded by private companies, such as the NHS, The Health Foundation, Innovate UK, European Commission. Dr Li is also the programme director of MSc Digital & Technology Solutions, and is the module convener of MSc Digital Health and Data Analytics.
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Academic lead and PI in the following grants, award and projects
1. The Health Foundation (Advancing Applied Analytics). Developing a patient event-based analytical framework to track and identify variation in clinical processes and patient outcome, £75k, August 2020 – August 202, 1936247.
2. Economic and Social Research Council (ESRC) award in applications and implications of Artificial Intelligence (AI). “Application and implication of machine learning: understanding and predicting healthcare resource usage and patient risk for improved population engagement”. £120k. 2019-2023.
3. Excellence in Impact Award, “Integrated Healthcare Information system for medical and care quality improvement”, O2RB (the University of Oxford, the Open University, Reading and Oxford Brookes) funded by Economic and Social Research Council Impact Acceleration Account, April 2018
4. Research Engagement and Impact Award, University of Reading. Predicting NHS outpatient attendance to reduce "Did-Not-Attend (DNA)" in Royal Berkshire NHS Foundation Trust, May 2020
5. Research contract. Royal Berkshire NHS Foundation Trust: “Predictive deep learning for clinical and operational intelligence”, £90k, 2017-2020.
6. Industry research contract. “Deep Learning from Electronic Patient Record and Knowledge Base for Predictive Clinical Support” £87k, 2017-2020.
7. Collaborative Innovation Fund (RBFT&UoR). Phenotyping patients living with Type 1 diabetes with detailed blood glucose variability and electronic patient record in the context of the continuous glucose monitoring system. The aim of this project is to provide insights of patient cohorts for personalised treatment. £8000, June 2019- Jan 2020
8. Collaborative Innovation Fund (RBFT&UoR). Early diagnosis of inflammatory arthritis using machine learning analysing GP referral letters, blood test and clinic letters to improve pre-hospital referral triage. £9,100, Jan 2020- August 2020
9. Collaborative Innovation Fund (RBFT&UoR). Can digital records determine disease phenotypes of diabetes kidney disease in the chronic and acute setting to influence service development to prevent admissions? £12,500, Jan 2020- June 2020
10. Collaborative Innovation Fund (RBFT&UoR). Predicting radiotherapy toxicity through electronic patient-reported outcomes (ePROMs) and electronic patient records (EPR) for personalised radiotherapy. £10,306, August 2020- July 2021
Digital Health and Data Analytics pathway
Programme Director MSc Digital and Technology Solutions
Telemedicine in practice in Future Proof Your Health Practice programme
- Artificial Intelligence and machine learning
- Information Systems
- Digital Health
- Advanced Analytics
- Finance Technology
- Decision Support System
- Digital Leadership and Strategy