Abstract

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.

Keywords

Precision medicinePersonalized medicineInferenceHealth careArtificial intelligenceConvergence (economics)Computer scienceData scienceMEDLINETranslational medicineMedicineBioinformaticsPathologyBiology

MeSH Terms

Artificial IntelligenceDelivery of Health CareForecastingGenetic Predisposition to DiseaseHumansPatient-Specific ModelingPrecision MedicineRisk AssessmentTranslational ResearchBiomedical

Affiliated Institutions

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Publication Info

Year
2020
Type
review
Volume
14
Issue
1
Pages
86-93
Citations
1426
Access
Closed

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Cite This

Kevin B. Johnson, Wei‐Qi Wei, Dilhan Weeraratne et al. (2020). Precision Medicine, AI, and the Future of Personalized Health Care. Clinical and Translational Science , 14 (1) , 86-93. https://doi.org/10.1111/cts.12884

Identifiers

DOI
10.1111/cts.12884
PMID
32961010
PMCID
PMC7877825

Data Quality

Data completeness: 90%