*Result*: AI-driven transformation of precision medicine: a comprehensive narrative review of key application areas, emerging paradigms, and future directions.
Title:
AI-driven transformation of precision medicine: a comprehensive narrative review of key application areas, emerging paradigms, and future directions.
Authors:
Zeng Q; Department of Pediatric Gastroenterology Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China., Huang C; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China.; National Office for Maternal and Child Health Surveillance of China, National Center for Birth Defect Surveillance of China, Department of Pediatrics, West China Second University Hospital, Chengdu, Sichuan, China., Zhu J; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, China.; National Office for Maternal and Child Health Surveillance of China, National Center for Birth Defect Surveillance of China, Department of Pediatrics, West China Second University Hospital, Chengdu, Sichuan, China.
Source:
Frontiers in public health [Front Public Health] 2026 Jan 08; Vol. 13, pp. 1656603. Date of Electronic Publication: 2026 Jan 08 (Print Publication: 2025).
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE
Imprint Name(s):
Original Publication: Lausanne : Frontiers Editorial Office
MeSH Terms:
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Contributed Indexing:
Keywords: artificial intelligence; deep learning; healthcare ethics; personalized treatment; precision medicine; remote monitoring; symbiotic artificial intelligence
Entry Date(s):
Date Created: 20260126 Date Completed: 20260126 Latest Revision: 20260128
Update Code:
20260130
PubMed Central ID:
PMC12823851
DOI:
10.3389/fpubh.2025.1656603
PMID:
41584179
Database:
MEDLINE
*Further Information*
*Objectives: This study aims to elucidate the pivotal role of Artificial Intelligence (AI) in driving the transformation of precision medicine, comprehensively analyzing how it reshapes healthcare systems from traditional diagnosis and treatment paradigms into personalized health management ecosystems.
Methods: A comprehensive narrative review was conducted to systematically synthesize and critically evaluate the innovative applications, paradigm shifts, and future prospects of AI across the entire precision medicine value chain. A comprehensive literature search was performed across multiple databases up to April 30, 2025, with a focus on the clinical implementation and breakthroughs of technologies such as deep learning (DL), machine learning (ML), and natural language processing (NLP).
Results: AI technologies have significantly enhanced the accuracy and efficiency of disease diagnosis through medical image analysis, genomics, and multimodal data fusion. At the treatment level, AI enables the development of personalized therapeutic plans and drug dosing optimization, while revolutionarily accelerating the drug development pipeline from discovery to clinical trials. Integrated with wearable devices and telemedicine platforms, AI facilitates full-cycle health monitoring. However, the clinical translation of AI faces challenges, including an uneven evidence base, insufficient model generalizability, and ethical concerns regarding data privacy, algorithmic fairness, and interpretability.
Conclusion: AI is a key driver of paradigm shift in precision medicine. To address existing challenges, future efforts should focus on generating more robust clinical evidence, adopting technologies like federated learning to ensure data privacy, and promoting the human-centered, collaborative framework of Symbiotic AI (SAI). By establishing sound ethical and governance structures, the deployment of AI technologies can be ensured to be not only efficient and advanced but also equitable and trustworthy, ultimately paving the way for an intelligent and inclusive healthcare ecosystem.
(Copyright © 2026 Zeng, Huang and Zhu.)*
*The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.*