Evolution of Artificial Intelligence in Healthcare: From Historical Milestones to Current Applications and Future Prospects in Hospital and Pharmaceutical Innovations

Abstract

Artificial Intelligence (AI) is reshaping healthcare by advancing diagnostics, treatment planning, drug discovery, and operational efficiency. Since its introduction in the 1950s, AI has progressed from early systems like MEDLARS, MYCIN, and INTERNIST-I to deep learning tools capable of specialist-level performance in medical imaging and predictive analytics. This paper traces AI’s evolution in healthcare, emphasizing historical milestones, current applications, and emerging directions. In the pharmaceutical domain, AI expedites drug discovery, enhances clinical trial efficiency, and personalizes treatment strategies. It also improves hospital workflows, patient adherence, and supply chain management. However, challenges persist, including data privacy, algorithmic transparency, and ethical concerns. Future efforts focus on interpretable AI models, robust data integration, and ethical frameworks. The integration of AI with technologies like blockchain and IoT holds promise for a more personalized, efficient, and accessible healthcare system.

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