The Intersection of Generative AI and Healthcare: Addressing Challenges to Enhance Patient Care

Abstract

This research analyses the evolving intersection of generative AI and healthcare. It explores the transformative potential of integrating generative AI in healthcare, particularly in process automation, patient care, patient monitoring, and diagnosis. However, the implementation of generative AI in healthcare faces challenges like medical privacy concerns, the possibility of errors and injuries, and regulatory compliance challenges. The research proposes solutions to the challenges of implementing generative AI to enhance patients’ health outcomes. The study demonstrates the importance of medical privacy and transparency in addressing privacy issues. Dealing with errors and injuries requires AI systems to be trained on complete data and quality oversight. Addressing regulatory compliance problems requires providers to be more proactive in engaging authorities and helping them understand the importance of creating AI-based laws in healthcare. The solutions allow researchers, providers, policymakers, and other stakeholders to fast-track the implementation of generative AI in healthcare while mitigating possible negative implications.

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