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Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Journal of Medical Internet Research · 2016 · Vol. 18(12) · pp. e323–e323

Wei Luo✉(Deakin University)Dinh Phung(Deakin University)Truyen Tran(Deakin University)Sunil Gupta(Deakin University)Santu Rana(Deakin University)Chandan Karmakar(Deakin University)Alistair Shilton(Deakin University)John Yearwood(Deakin University)Nevenka Dimitrova(Philips (United States))Tu Bao Ho(Japan Advanced Institute of Science and Technology)Svetha Venkatesh(Deakin University)Michael Berk(Deakin University)

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Abstract

A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community.

Machine Learning in Healthcare Artificial Intelligence in Healthcare Explainable Artificial Intelligence (XAI)Multidisciplinary approachComputer scienceData scienceArtificial intelligenceMachine learningMedicinePsychology