What are the current research gaps in ap... - tlooto, The Most Powerful AcademicGPT

What are the current research gaps in applying generative AI for personalized medicine[1], and how can we address challenges related to data bias[2], interpretability[3], and regulatory approval[4]? Explanation of reference selection: - Reference [1] focuses specifically on AI-generated personalized therapy regimens based on genetic and medical history, directly addressing the application of generative AI in personalized medicine. - Reference [2] highlights the problem of data bias in generative AI healthcare applications and suggests future research directions to mitigate bias. - Reference [3] proposes a data-management perspective for verifying generative AI outputs, which is crucial for improving model interpretability and trustworthiness. - Reference [4] provides an overview of regulatory compliance challenges in digital health contexts and discusses measures to ensure generative AI systems meet existing health regulations.