Artificial intelligence for medicine 2025: Navigating the endless frontier

Ji Dai; Huiyu Xu; Tao Chen; Tao Huang; Weiqi Liang; Rui Zhang; Gengxin Xu; Zhiting Zhang; Le Xue; Yi Gao; Mingyue Zheng; Guoshuang Feng; Zhe Zhang; Jinle Tang; Jian Zhan; Yaoqi Zhou; Ye Li; Yixue Li; Mei Tian

doi:10.59717/j.xinn-med.2025.100120

The Innovation Medicine > 2025 Vol. 3 > No. 1 > 100120

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Artificial intelligence for medicine 2025: Navigating the endless frontier

1.
Shenzhen Technological Research Center for Primate Translational Medicine, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
2.
Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China
3.
Department of Gastrointestinal and hernia surgery, Ganzhou Hospital-Nanfang Hospital, Southern Medical University, Ganzhou 341000, China
4.
Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
5.
CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China
6.
Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
7.
Huashan hospital, Fudan University, Shanghai 200040, China
8.
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518037, China
9.
Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
10.
Big Data Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
11.
Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
12.
Ribopeutic Inc., Guangzhou 510710, China
13.
Guangzhou National Laboratory, Guangzhou 510000, China
14.
Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
15.
Human Phenome Institute, Fudan University, Shanghai 200438, China
16.
Department of Nuclear Medicine and PET-CT Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
17.
These authors contributed equally

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Corresponding authors: huangtao@sibs.ac.cn (T.H.); zhouyq@szbl.ac.cn (Y.Z.); ye.li@siat.ac.cn (Y.L.); li_yixue@gzlab.ac.cn (Y.L.); tianmei@fudan.edu.cn (M.T.)
Received Date: 14 February 2025

Accepted Date: 20 February 2025

Published Online: 21 February 2025

The Innovation Medicine 3(1), https://doi.org/10.59717/j.xinn-med.2025.100120 | Cite this article

GRAPHICAL ABSTRACT

GRAPHICAL ABSTRACT

PUBLIC SUMMARY

PUBLIC SUMMARY
1. AI helps us understand the complex medical phenotypes and diverse data.
  
  AI forecasts the forthcoming medical innovations in surgical robots and BCI.
  
  AI will solve the low birth rate and aging population challenges of human beings.

ABSTRACT

ABSTRACT

Artificial intelligence (AI) is driving transformative changes in the field of medicine, with its successful application relying on accurate data and rigorous quality standards. By integrating clinical information, pathology, medical imaging, physiological signals, and omics data, AI significantly enhances the precision of research into disease mechanisms and patient prognoses. AI technologies also demonstrate exceptional potential in drug development, surgical automation, and brain-computer interface (BCI) research. Through the simulation of biological systems and prediction of intervention outcomes, AI enables researchers to rapidly translate innovations into practical clinical applications. While challenges such as computational demands, software development, and ethical considerations persist, the future of AI remains highly promising. AI plays a pivotal role in addressing societal issues like low birth rates and aging populations. AI can contribute to mitigating low birth rate issues through enhanced ovarian reserve evaluation, menopause forecasting, optimization of Assisted Reproductive Technologies (ART), sperm analysis and selection, endometrial receptivity evaluation, fertility forecasting, and remote consultations. In addressing the challenges posed by an aging population, AI can facilitate the development of dementia prediction models, cognitive health monitoring and intervention strategies, early disease screening and prediction systems, AI-driven telemedicine platforms, intelligent health monitoring systems, smart companion robots, and smart environments for aging-in-place. AI profoundly shapes the future of medicine.

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Dai J., Xu H., Chen T., et al. (2025). Artificial intelligence for medicine 2025: Navigating the endless frontier. The Innovation Medicine 3:100120. https://doi.org/10.59717/j.xinn-med.2025.100120

Dai J., Xu H., Chen T., et al. (2025). Artificial intelligence for medicine 2025: Navigating the endless frontier. The Innovation Medicine 3:100120. https://doi.org/10.59717/j.xinn-med.2025.100120

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