Danielle Newby
B.Sc, PhD
Postdoctoral Researcher
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 jointly led by Sir Professor Simon Lovestone and Professor Noel Buckley. I am currently the lead of the Prevention working group for the DEMON network (http://demondementia.com/) which is a network applying data science and artificial intelligence to dementia research.
My main research interests are:
- Understanding and characterizing risk factors for dementia
- Drug repurposing for dementia prevention
- Causal inference and machine learning for dementia
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 am collaborating 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.
Recent publications
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Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multi-national network cohort study
Journal article
LANE JCE. et al, (2020), Rheumatology
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Risk of hydroxychloroquine, alone and in combination with azithromycin in the treatment of Rheumatoid Arthritis: a multi-national, retrospective study
Journal article
LANE J., (2020), Lancet Rheumatology
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Journal article
LANE J. et al, (2020)
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Journal article
Newby D. et al, (2020), Alzheimers Res Ther, 12
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Conference paper
Stacey J. et al, (2018), VALUE IN HEALTH, 21, S329 - S329