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September 10, 2025

Automated decision support systems for healthcare: An AI-powered approach

Key Points

AI-powered decision support systems enhance diagnosis and treatment planning in diverse clinical settings.
Key studies demonstrate how clinical data utilization improves accuracy in prognosis and decision-making.
Theoretical models and benchmark experiments reveal significant deployment challenges like trust and explainability.
This exploration underscores the importance of maintaining human oversight and data governance in clinical applications.

Abstract

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 (Wed,) studied this question.

synapsesocial.com/papers/68c1a8fe54b1d3bfb60e1bc6 — DOI: https://doi.org/10.30574/wjaets.2025.16.1.1240

Automated decision support systems for healthcare: An AI-powered approach

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