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The Promises and Perils of Clinical Decision Support Artificial Intelligence
Jorge Cervantes1, Bhavya Vashi1
1Dr. Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Fort Lauderdale, Florida, USA.
None:
Evidence-based clinical decision support artificial intelligence (AI) is rapidly expanding, but its safe and effective use depends on rigorous validation, trustworthy evidence sources and careful integration into clinical workflows. Current available systems show strong potential to improve diagnostic accuracy, reduce clinician workload and possibly benefit patient care, but challenges remain before its real-world adoption. We must be responsible in its integration to ensure AI truly strengthens clinical judgment. This article is a viewpoint of AI tools for clinical decision support, addressing a rapidly evolving field and provides insights that are useful for clinicians and educators in clinical settings. When used within appropriate medical training, AI may help augment diagnostic accuracy and improve efficiency. Nevertheless, while AI offers promising features, it also presents ethical and reliability challenges, which may negatively affect the medical professional identity.
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