Generative AI in Personalized Medicine
Sreedeep Dey · 2025
Personalized medicine is based on the genetic makeup and clinical profiles of the individual patient. However, it demands a large amount of data collection and resources and reveals difficulties in patient privacy. Generative AI revolutionizes patient-centered healthcare. It provides accuracy and privacy-preserving patient data and acts as a solution. In this chapter, we emphasize the importance of deep generative models (DGMs) in the field of precision medicine. DGMs work by investigating bioinformatics, clinical informatics, medical imaging, and early diagnosis. We summarize how AI is involved in precision medicine and how DGMs are being applied in synthetic data production. With the help of generative adversarial networks (GANs), DGMs improve synthetic data generation and increase accuracy with privacy. Driven by the principle of pharmacogenomics and treatments based on algorithms, personalized medicine focuses on combining genetic, transcriptomic, proteomic, epigenetic, and lifestyle aspects of a patient. Customized deep learning architectures for personalized treatment plans are also explored in this chapter. Using wearable data generative AI provides personalized care suggestions. These prospectives help the model to improve overall electronic health records (EHRs). Proper management of ethical concerns and ensuring the quality of the data content is crucial. Moreover, how foundation models and generative AI are transforming the field of personalized medicine is emphasized in this chapter. For the betterment of promising treatments, further research and exploration are crucial.