Artificial Intelligence in Evidence-based Medicine: Challenges and Opportunities

Abstract

Evidence-based Medicine (EBM) is facing a new challenge in applying Artificial Intelligence (AI) for better services. Here the fundamental question is: can AI be used as a human intelligence amplifier to make better evidence-based medical decisions? This argument can only be answered if AI-supported decisions are compared and contrasted with those of human experts, and if the implementation of AI-enabled Evidence-Based Medicine (AiEBM) can be explained or justified using the available evidence and experience. In this paper, we propose AiEBM as a human-centered approach to be integrated into processes of healthcare systems, thereby increasing the credibility of the clinical decision support systems. We provide insights into the applicability of AI and its challenges and opportunities in EBM. The AaaS (AI as a Service) and high-order reasoning facilitated by machine learning and AI for medical decisions will be discussed.