Artificial intelligence for personalised medicine
Advances in artificial intelligence (AI) present an opportunity to optimise pathways of diagnosis and prognosis, and to develop personalised strategies for treatment, through the utilisation of large datasets. For instance, analyses which capture potential risk-factors – from underlying genetics to specific environments – could aid in the development of prophylactic strategies, and more accurate diagnosis. In addition, both structural and functional imaging techniques can provide patient specific insight into current health, and inform treatment.
This Collection will present papers that demonstrate innovations in the use of AI in health, from personalised assessment of risk, to improved diagnostic and treatment protocols.
Editors
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Michael D. Abramoff
University of Iowa, USA
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Nicholas Furnham
London School of Hygiene and Tropical Medicine, UK
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Reiko Tanaka
Imperial College London, UK
