This review examines the implementation of AI-driven decision support systems in healthcare, highlighting key challenges and advancements.
Artificial Intelligence (AI) has become a cornerstone of modern healthcare transformation, particularly through the development of Automated Decision Support Systems (DSS). These systems harness clinical data to assist in diagnosis, prognosis, and treatment planning. This review explores the evolution, implementation, and evaluation of AI-powered DSS across multiple clinical domains including radiology, emergency medicine, oncology, and mental health. Drawing on key studies and technological advancements, we present a theoretical model, benchmark comparative experiments, and discuss deployment challenges such as explainability, trust, and data governance. This article offers a roadmap for scaling AI in clinical environments while preserving safety, transparency, and human oversight.
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Bhanuvardhan Nune (2025) studied this question.
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