Leveraging Artificial Intelligence for Enhanced Clinical Decision Support Systems (CDSS)
DOI:
https://doi.org/10.35516/jmj.v59i2.2889Keywords:
Artificial Intelligence (AI), Clinical Decision Support Systems (CDSS), Digitalization in Healthcare, Medical Diagnostics, Epistemic Challenges, Machine Learning AlgorithmsAbstract
The integration of Artificial Intelligence (AI) into healthcare is driven by digitalization, aiming to enhance early disease diagnosis and treatment. Effective digital transformation in healthcare relies on assessing AI's potential and ensuring seamless collaboration between medical professionals and AI specialists. Clinical Decision Support Systems (CDSS) are crucial for assisting healthcare providers with decision-making. This review provides an overview of AI's role in healthcare, focusing on CDSS, and addresses epistemic concerns in their development. It highlights the need for alignment between technology and practitioners, emphasizing collaboration and cognitive responsibilities in patient profiling. A comprehensive search in PubMed, Scopus, and Google Scholar using keywords like AI, CDSS, and Machine Learning consolidates insights on evaluating AI-enabled CDSS across design, development, selection, implementation, and monitoring stages. The review also discusses practical evaluation approaches, AI performance indicators, and the importance of explainable CDSS for fostering direct patient connections.
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