Author(s) :

Mukund Desai.

Volume/Issue :

Abstract :

The integration of Artificial Intelligence (AI) into diagnostic tools has emerged as a transformative force in modern healthcare. AI-driven diagnostic systems offer the potential to improve accuracy, reduce diagnostic errors, and enhance clinical efficiency. This paper provides a comprehensive evaluation of smart diagnostic tools powered by AI, exploring their capabilities, limitations, and impact on healthcare outcomes. It delves into key technological advancements, including machine learning, deep learning, and natural language processing, that underpin these systems. The paper also examines real-world applications across various medical specialties, highlighting successes, challenges, and areas where AI has reshaped clinical diagnostics. Furthermore, it addresses critical considerations such as algorithmic bias, data quality, regulatory frameworks, and integration into clinical workflows. Concluding with recommendations for future research and implementation strategies, this paper aims to inform stakeholders about the responsible deployment of AI-driven diagnostic tools to achieve enhanced diagnostic accuracy in patient care.

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