Beyond the Algorithm: Re-centering Clinical Diagnosis in the Age of Artificial Intelligence

Abstract

A BSTRACT The rise of artificial intelligence (AI) is redefining clinical diagnosis, transforming a traditionally human-centered process into one increasingly supported by data-driven prediction. AI systems, particularly those based on machine learning and neural networks, demonstrate remarkable accuracy in pattern recognition, early disease detection, and risk stratification. However, diagnosis extends beyond prediction to include judgment – an inherently human function shaped by clinical experience, ethical reasoning, and patient context. Overreliance on AI risks erosion of clinical acumen, deskilling of trainees, and weakening of the doctor–patient relationship. In settings like India, where trust in healthcare systems is already under strain, uncritical adoption may further undermine clinician authority. Moreover, AI remains vulnerable to data bias, opacity, and misinformation. A balanced approach is essential: integrating AI as an adjunct while preserving clinical reasoning, empathy, and accountability. The future of diagnosis lies in synergy – where algorithms assist, but clinicians retain decisional primacy and responsibility.

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