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Abstract
The fast adoption of electronic health records (EHR) has provided the field of medicine with an unprecedented
opportunity for finding patterns and insights that can influence both policy and practice of care. A patient's
EHR is usually a sequence of mixed-type (i.e., numeric and nonnumeric fields) multimodal (e.g., diagnosis
codes, medications, measurements, and more) data, that occur in regular intervals. While expert-defined
features/markers extracted from EHR at a baseline (e.g., time of certain diagnoses, or age) have led to
relatively accurate prediction of certain outcomes, the ability of such approaches in leveraging the full
richness of EHR is limited. Therefore, in recent years, there has been a surge in the development of models
that can automatically determine the optimal combination of EHR data for creating both general-purpose and
task-specific predictors/markers. In this talk, I will introduce some of the latest developments in the
field of machine learning (mostly, deep learning) and EHR.
I will introduce BEHRT (Liu and Rao et al 2020, Nature Sci Rep), which is inspired by the latest developments
in the field of natural language processing (NLP) and has been shown to provide superior accuracy in the
prediction of disease onsets, when trained and tested on millions of patients' linked EHR data from
the UK (i.e., CPRD). Furthermore, I will explore additional ideas on how such deep learning models can
close the gap between predictive models and clinical practice, and help improve the personalised risk
models and complex diseases patterns such as multimorbidity.
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Bio
Reza is currently the chief scientist at AIG, and a principal investigator (in machine learning and medicine)
at Deep Medicine program of The University of Oxford. His current research at Oxford is focused on
probabilistic machine learning, and deep sequence models, for biomedical informatics, population health,
and precision medicine; more specifically, he is interested in using machine learning for the development
of personalised health predictions and recommendations, and an improved understanding of multimorbidity.
Reza's team at AIG (i.e., Investments AI) is a group of scientists, engineers, designers and product
managers/strategists, primarily focused on the development of AI-first products in the FinTech space.
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