Application of Artificial Intelligence Large Models in Healthcare:a Survey

Corresponding author: GE Xiaoling, xlge@fudan.edu.cn

DOI: 10.12201/bmr.202408.00039

•  

  Abstract: The healthcare field has abundant multimodal data and open and diverse medical and health scenarios, which is one of the most promising fields for the application of artificial intelligence large models. Based on hardware, equipment and model framework, the AI large models utilizes medical text, medical image or medical multimodal datasets to carry out pre-training, fine-tuning, evaluation, optimization and utilization, thus achieves model building. The healthcare AI large model has been successfully applied in auxiliary diagnosis and treatment, medical imaging research, health management, biomedical research, drug research, medical examination and education, etc.However its also challenged by data security risks, moral and ethical risks, and technical risks. To regularize the development of AI large model technology, Some countries have formulated relevant laws, regulations, and standards . Opportunities and challenges coexist in healthcare cooperation with artificial intelligence, and artificial intelligence large model technology still needs to be continuously optimized and developed to promote deeper integration with the healthcare field.

  Key words: artificial intelligence; large model; healthcare; intelligent application

  Submit time: 20 August 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
• html

• 图表

• ZhengYanli, Han Fuhai, LI Shuyu, SU Wenxing. Application Status and Prospect of Artificial Intelligence Large Models in Medicine. 2023. doi: 10.12201/bmr.202312.00027

  shisenzhong. Analysis of the Risks and Governance Strategies for the Application of Generative Artificial Intelligence (GAI) in Primary Healthcare. 2024. doi: 10.12201/bmr.202408.00053

  Cai. Clinical Application and Technique of Smart Medical. 2021. doi: 10.12201/bmr.202012.00013

  Shi Chenghao, Tu Xinyi, Shi Jiawei, Chen Hongshuang, Wang Qinlu, Zou Haiou. A Scoping Review of the Application of Large Language Models in Clinical Practice. 2024. doi: 10.12201/bmr.202406.00001

  Yufan Zhu, Xin Zhao, Zhiqiang Yang, Houcheng Zhong, Lin Cai, Yuanlong Xie. Prospect of the Training Model for Artificial Intelligence + Medicine Inter-disciplinary Talents. 2020. doi: 10.12201/bmr.202008.00010

  xiejunxiang. The composition of Key Technologies and Application in Medical Artificial Intelligence. 2020. doi: 10.12201/bmr.202005.00243

  yanwencheng, lijunzhen, chenmei, 卢艳红. Artificial Intelligence for Stomatology: Application in Dental Endodontics. 2021. doi: 10.12201/bmr.202102.00003

  Dong Kun, Yang Fen, Yang Yang. Application and Thinking of Artificial Intelligence in General Practitioner Training. 2023. doi: 10.12201/bmr.202305.00011

  SiWei, XuTing, LinJiayue, Cao Wenting, ZhuAiyong. A review of artificial intelligence technology in the screening of cognitive impairment. 2024. doi: 10.12201/bmr.202407.00048

  Lin Jinyin, Lu Changfeng. Main Stakeholder analysis of the application of artificial intelligence in the field of Medical University Library. 2023. doi: 10.12201/bmr.202303.00001

• ID	Submit time	Number	Download
  1	2024-08-08	bmr.202408.00039V1	Download

• Public  Anonymous  To author only Submit Comments