AI-CDSS can be integrated into healthcare to improve the quality of care for patients, reduce differences in treatment, and maximize the usage of resources.For instance, such systems can offer meaningful insights into actionable evidence through the help of advanced data analytics and machine learning.All this, however, brings a plethora of challenges when trying to integrate AI into a clinical environment, such as ethical concerns about algorithmic bias, strong regulatory frameworks, and changes in work�low.Published sources were used between 2014 and 2024 in PubMed, Scopus, and Google Scholar databases.The review encompasses randomized controlled trials, observational studies, and metaanalyses but excludes non-clinical encounters, conference proceedings, and editorials.The �ive main themes of AI and clinical decision-making hinge on the need for XAI to be transparent and the role that multidisciplinary specialties contribute.The �indings presented here speak to the high promise that AI-CDSS offers in various health-related areas but point out the need for regulatory measures, ethical issues, and user interfaces for effective utilization in clinical practice. I.
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A 2025 study studied this question.