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Vol. 1 (2024)
Open Access Review

The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects

by Jing-Min Yang 1,*  and  Jingyi Li 2
1
Hubei Bioinformatics & Molecular Imaging Key Laboratory, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
2
Affiliated Hospital of North China University of Science and Technology, Tangshan 063000, Hebei, China.
*
Author to whom correspondence should be addressed.
AI  2024 1(1):4; https://doi.org/10.0000/0003
Received: 19 November 2024 / Accepted: 1 December 2024 / Published Online: 6 December 2024
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Abstract

The rapid advancement of artificial intelligence (AI) technologies, particularly the emergence of large models, has ushered in unprecedented opportunities within the medical field. The application of open-source large models enables more efficient utilization of data in medical research and clinical practice, enhancing the precision of diagnosis and treatment. This review outlines the current status of AI large models in medicine, exploring their potential in disease prediction, image analysis, and personalized treatment. Furthermore, it analyzes the challenges faced by these technologies and discusses future development directions, emphasizing the need for improved methodologies and collaborative efforts to maximize their impact on healthcare.

Keywords: Artificial Intelligence; Large Models; Open-Source; Medicine; Disease Prediction; Imaging Analysis; Personalized Treatment;
Copyright: © 2024 by Yang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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APA Style
Yang, J., & Li, J. (2024). The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI, 1(1), 4. doi:10.0000/0003
ACS Style
Yang, J.; Li, J. The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI, 2024, 1, 4. doi:10.0000/0003
AMA Style
Yang J, Li J. The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI; 2024, 1(1):4. doi:10.0000/0003
Chicago/Turabian Style
Yang, Jing-Min; Li, Jingyi 2024. "The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects" AI 1, no.1:4. doi:10.0000/0003

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APA Style
Yang, J., & Li, J. (2024). The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI, 1(1), 4. doi:10.0000/0003
ACS Style
Yang, J.; Li, J. The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI, 2024, 1, 4. doi:10.0000/0003
AMA Style
Yang J, Li J. The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects. AI; 2024, 1(1):4. doi:10.0000/0003
Chicago/Turabian Style
Yang, Jing-Min; Li, Jingyi 2024. "The Open-Source Applications of Large AI Models in Medicine: Current Status and Future Prospects" AI 1, no.1:4. doi:10.0000/0003

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