GenAI Use Cases and Challenges in Healthcare with Dr. Girish Nadkarni

In this episode of AI Explained, Dr. Girish Nadkarni discusses the applications of AI in healthcare. He differentiates between the use of generative AI in back-office tasks, such as automating appointments and billing, and its slow integration into clinical settings. He highlights the potential of ambient AI to reduce the administrative burden on physicians, allowing them to focus more on patient interaction. Dr. Nadkarni also addresses the use of AI in predictive analysis, such as risk prediction and sepsis detection, emphasizing the importance of safety, effectiveness, and ethical considerations. He explores the interplay between classical ML and generative AI, including the use of generative AI for predictive purposes and the concept of AI agents in medicine. The conversation touches on the challenges of AI hallucinations and the need for risk-based approaches and governance processes to ensure accurate and reliable AI outputs. Dr. Nadkarni envisions a future of personalized medicine, where AI-driven systems can create tailored treatments based on individual genetic and clinical data, and he also discusses the potential for AI to improve healthcare accessibility in low-income countries.