![]() ![]() This study discusses the impact and integration of these different fields in the scope of precision medicine and how they can be used in preventing and predicting acute or chronic diseases. When considering the intersection of traditionally distinct arenas of medicine, that is, artificial intelligence, healthcare, clinical genomics, and pharmacogenomics-what ties them together is their impact on the development of precision medicine as a field and how they each contribute to patient-specific, rather than symptom-specific patient outcomes. Compared to the symptom-driven approach in medicine, precision medicine considers the critical fact that all patients do not react to the same treatment or medication in the same way. It makes use of clinical data associated with the patient as well as their multi-omics/genomic data to reach a conclusion regarding how a physician should proceed with a specific treatment. Precision medicine has greatly aided in improving health outcomes using earlier diagnosis and better prognosis for chronic diseases. Habiba Abdelhalim, Asude Berber, Mudassir Lodi, Rihi Jain, Achuth Nair, Anirudh Pappu, Kush Patel, Vignesh Venkat, Cynthia Venkatesan, Raghu Wable, Matthew Dinatale, Allyson Fu, Vikram Iyer, Ishan Kalove, Marc Kleyman, Joseph Koutsoutis, David Menna, Mayank Paliwal, Nishi Patel, Thirth Patel, Zara Rafique, Rothela Samadi, Roshan Varadhan, Shreyas Bolla, Sreya Vadapalli and Zeeshan Ahmed Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine ![]()
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