ABSTRACT Background With the increasing integration of digital technologies, precision medicine, and artificial intelligence into contemporary evidence‐based medicine (EBM), a range of novel methodological approaches, such as real‐world data, synthetic control arms, N‐of‐1 trials, and large‐scale predictive models, have been introduced into clinical decision‐making as complementary forms of practice beyond traditional randomized controlled trials. Although these approaches have gained traction in both technical implementation and institutional adoption, their epistemic status as “evidence” and their appropriate positioning within the existing EBM hierarchy remain insufficiently examined. Objective This study adopts a perspective from philosophy of science and epistemology to analyze the inferential structures and causal assumptions underpinning these emerging evidence forms, and to assess their applicability in guiding clinical action, supporting explanation, and bearing normative responsibility. Results We argue that in the post‐EBM era, the concept of evidence must evolve beyond a monolithic methodological paradigm toward a more pluralistic and practice‐oriented framework, which is capable of addressing the growing complexity, uncertainty, and individual variability in modern medical decision‐making.
Wenxiu Qi (2026) studied this question.