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I am an early career dementia researcher with an interdisciplinary background in epidemiology, machine learning, and pharmacology. Since April 2016, I have been working as a post-doctorate researcher in the informatics team of the Translational Neuroscience and Dementia Research Group. I am currently the lead of the Prevention working group for the DEMON network, which is a network applying data science and artificial intelligence to dementia research.
My main research interests are:
- Drug repurposing for dementia prevention - finding drugs and understanding mechanisms
- Understanding and characterizing risk factors for dementia - how they relate and interact
- Causal inference and machine learning for dementia - using the best and newest methods
My main areas of research within the team involve the analysis of real-world data such as medical electronic health records using traditional statistical approaches and machine learning. By using a wide variety of existing datasets and methods we can triangulate evidence to understand more about what causes dementia and what we can do to intervene. By understanding these relationships this will provide an evidence base to support public health intervention for dementia prevention.
I also collaborate on numerous health and social care projects within and outside the Department of Psychiatry including providing statistical expertise and data analysis to gain insights into young adult mental health.
Lane JCE. et al, (2020), Rheumatology (Oxford)
High Blood Pressure and Risk of Dementia: a Two-Sample Mendelian Randomization study in the UK Biobank
SPROVIERO W. et al, (2020), Biological Psychiatry
Risk of hydroxychloroquine, alone and in combination with azithromycin in the treatment of Rheumatoid Arthritis: a multi-national, retrospective study
LANE J., (2020), Lancet Rheumatology
Lane JCE. et al, (2020)
LANE J. et al, (2020)