Bridging paradigms: hybrid mechanistic-discriminative predictive models

Orla M Doyle, Krasimira Tsaneva-Atansaova, James Harte, Paul A Tiffin, Peter Tino, Vanessa Díaz-Zuccarini

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Many disease processes are extremely complex and characterized by multiple stochastic processes interacting simultaneously. Current analytical approaches have included mechanistic models and machine learning (ML), which are often treated as orthogonal viewpoints. However, to facilitate truly personalized medicine, new perspectives may be required. This paper reviews the use of both mechanistic models and ML in healthcare as well as emerging hybrid methods, which are an exciting and promising approach for biologically based, yet data-driven advanced intelligent systems.
Original languageEnglish
Pages (from-to)735-742
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Issue number3
Publication statusPublished - Mar 2013


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