RT Journal Article SR Electronic T1 Evidence-based medicine and machine learning: a partnership with a common purpose JF BMJ Evidence-Based Medicine JO BMJ EBM FD BMJ Publishing Group Ltd SP bmjebm-2020-111379 DO 10.1136/bmjebm-2020-111379 A1 Ian Scott A1 David Cook A1 Enrico Coiera YR 2020 UL http://ebm.bmj.com/content/early/2020/08/19/bmjebm-2020-111379.abstract 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?