PT - JOURNAL ARTICLE AU - Ian Scott AU - David Cook AU - Enrico Coiera TI - Evidence-based medicine and machine learning: a partnership with a common purpose AID - 10.1136/bmjebm-2020-111379 DP - 2020 Aug 19 TA - BMJ Evidence-Based Medicine PG - bmjebm-2020-111379 4099 - http://ebm.bmj.com/content/early/2020/08/19/bmjebm-2020-111379.short 4100 - http://ebm.bmj.com/content/early/2020/08/19/bmjebm-2020-111379.full AB - From its origins in epidemiology, evidence-based medicine has promulgated a rigorous approach to assessing the validity, impact and applicability of hypothesis-driven empirical research used to evaluate the utility of diagnostic tests, prognostic tools and therapeutic interventions. Machine learning, a subset of artificial intelligence, uses computer programs to discover patterns and associations within huge datasets which are then incorporated into algorithms used to assist diagnoses and predict future outcomes, including response to therapies. How do these two fields relate to one another? What are their similarities and differences, their strengths and weaknesses? Can each learn from, and complement, the other in rendering clinical decision-making more informed and effective?