Effective integration of artificial intelligence (AI) in community cancer care hinges on overcoming technical, clinical, economic, regulatory, and ethical challenges, as emphasized by Dr. Kashyap Patel during the MiBA Community Summit. AI has the potential to enhance personalized care by rapidly analyzing clinical factors, reducing adverse treatment effects, and improving diagnostic accuracy. However, issues such as data privacy, algorithm bias, and acceptance among healthcare providers hinder its widespread adoption. To address these challenges, Patel suggests piloting AI programs focused on cancer screening and developing data integration infrastructures. Over the next few years, executing AI-enhanced workflows and monitoring systems will be essential for implementing precision medicine approaches. Future advancements in AI technology will focus on integrating multiomics data and enabling real-time patient monitoring, all while ensuring patient privacy. As the landscape of targeted therapies evolves, AI can streamline processes for appropriate testing and treatment options, ultimately improving outcomes in community cancer care.
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