Precision Medicine, AI, and the Future of Personalized Health Care
By Kevin B. Johnson, Wei-Qi Wei, D. Weeraratne, M. Frisse, K. Misulis, K. Rhee, Juan Zhao, J. Snowdon. Clinical and Translational Science, 2020
1,308 citations recorded by the source corpus.
The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less‐common responses to treatment or unique healthcare needs. AI leverages sophisticated computation and inference to generate insights, enables the system to reason and learn, and empowers clinician decision making through augmented intelligence. Recent literature suggests that translational research exploring this convergence will help solve the most difficult challenges facing precision medicine, especially those in which nongenomic and genomic determinants, combined with information from patient symptoms, clinical history, and lifestyles, will facilitate personalized diagnosis and prognostication.
Subfields: Artificial Intelligence, Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/406289a706af2e00006a5823f245ef7bcd811681
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Citations in the corpus
- Revolutionizing healthcare: the role of artificial intelligence in clinical practice (2023, background): “The potential applications of AI in assisting clinicians with treatment decisions, particularly in predicting therapy response, have gained recognition [49].”
- ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns (2023, background): “The promising utility of AI in health care has been outlined previously with possible benefits in personalized medicine, drug discovery, and the analysis of large datasets aside from the potential applications to improve diagnosis and clinical decisions [17,18].”
- Bias in artificial intelligence algorithms and recommendations for mitigation (2023, background): “Moreover, with the advances in precision medicine, AI algorithms may assist in further enhancing personalized medicine and optimal care [9].”
- Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design (2023, background): “As a result, there is a need for an improved interpretability and explainability of AI models, to ensure that their predictions can be understood and used effectively [221,222].”