Multi-Agent Learning for Adaptive Clinical Decision-Making

It is still a long way before Artificial Intelligence (AI) can replace human clinicians in healthcare. AI may eventually assist in every aspect of the healthcare ecosystem, but introducing an interactive and fully-fledged personal assistant capable of communicating, storing, and learning selectively as a clinician remains an uncharted journey. The interaction between clinicians and technology is, in fact, becoming more profound as the technology becomes necessary for interpreting all sorts of clinical data. Still, the final decision lies in the clinician's cognitive abilities, emotional intelligence, and life knowledge. AI, however, can contribute to any part of the decision-making process under heavy supervision, as the direct impact of a mistake can affect human lives. Therefore, AI can be considered an informative tool during the decision-making process. Nevertheless, there is still much room for improving and writing adaptive tools that can be chosen or rejected by a user or a group of users.