Precision Medicine, AI, and the Future of Personalized Health Care

Прецизионная медицина, искусственный интеллект и будущее персонализированного здравоохранения
Wei‐Qi Wei, Juan Zhao, Kyu Rhee, Kevin B. Johnson, Jane Snowdon, Dilhan Weeraratne, Mark E. Frisse, Karl E. Misulis
2020-09-22

artificial intelligenceaugmented intelligencepersonalized diagnosispersonalized health careprecision medicine
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.
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AI contributes sophisticated computation, inference, learning, and augmented intelligence to support clinician decision-making.
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Further translational research is needed to realize the potential of AI-enabled precision healthcare.
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Integrating genomic and nongenomic determinants with symptoms, clinical history, and lifestyle information may address major challenges in precision medicine.
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Precision medicine identifies patient phenotypes associated with uncommon treatment responses or distinctive healthcare needs.
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The convergence of artificial intelligence and precision medicine could transform healthcare by enabling more personalized diagnosis, prognosis, and treatment.

AI-integrated precision medicine and personalized health care systems

The use of AI to integrate genomic, nongenomic, clinical, symptom, and lifestyle information for personalized diagnosis and prognostication

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Publication Date
2020-09-22
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Authors
Wei‐Qi Wei
Juan Zhao
Kyu Rhee
Kevin B. Johnson
Jane Snowdon
Dilhan Weeraratne
Mark E. Frisse
Karl E. Misulis
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