Abstract

Artificial Intelligence (AI) has undergone transformative advancements in healthcare since its inception, evolving from early expert systems to sophisticated deep learning models. This paper provides a comprehensive historical overview of AI in healthcare, tracing its development from the 1960s with early systems like MYCIN to contemporary applications involving deep learning and big data. Key milestones include the expansion of expert systems in the 1980s, the integration of machine learning and electronic health records in the 2000s and the revolutionary impact of deep learning on medical imaging and genomics in the 2010s and beyond. The benefits of AI in healthcare are substantial, encompassing enhanced diagnostic accuracy, personalized treatment plans and streamlined clinical workflows. AIdriven tools have significantly improved patient care through predictive analytics and virtual health assistants, leading to better outcomes and more efficient healthcare delivery. Furthermore, AI is crucial in expanding access to healthcare for underserved populations, with innovations in telemedicine, mobile health solutions and affordable diagnostic tools addressing disparities in healthcare access. This paper concludes by highlighting the potential future advancements in AI, which promise to further drive innovation and improve global health outcomes. As AI continues to evolve, its integration into healthcare systems is expected to enhance both patient and provider experiences, ultimately contributing to a more equitable and effective healthcare landscape.