A roadmap for medical large language models: a review of foundations, applications, and challenges

Yu-Yang Sha; Li Yu; Ze-Hui Lin; Amandeep Kaur; Yan-Yan Lou; Shivanand S Gornale; Tian-Yu Zhang; Ling Shing Wong; Zhi-Wen Wang; Yan Yan; Xian-Bin Zhang; Rui Hong; Ka Li; Sio Kei Im; Paulo de Carvalho; Tao Tan; Ke-Feng Li

doi:10.1016/j.mmr.2026.100050

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A roadmap for medical large language models: a review of foundations, applications, and challenges

REVIEW | Updated：2026-08-21

- A roadmap for medical large language models: a review of foundations, applications, and challenges
- A roadmap for medical large language models: a review of foundations, applications, and challenges
- 军事医学研究（英文） 2026年
- Affiliations：
  
  Faculty of Applied Sciences, Macao Polytechnic University, Macau 999078, Macao SAR, China
  Department of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, China
  Department of Computer Science and Technology, School of Engineering and Technology, Central University of Punjab, Bathinda, Punjab 151401, India
  Division of Hematology and Oncology, Mayo Clinic, Jacksonville, FL 32224, USA
  Department of Computer Science, School of Mathematics and Computing Sciences, Rani Channamma University, Belagavi, Karnataka 590016, India
  Department of Radiology, the Netherlands Cancer Institute, Amsterdam 1066 CX, the Netherlands
  Faculty of Health and Life Sciences, INTI International University, Nilai, Negeri Sembilan 71800, Malaysia
  School of Nursing, Peking University, Beijing 100191, China
  Guangdong-Hong-Kong-Macao University Joint Laboratory of Interventional Medicine, the Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai 519000, Guangdong, China
  Department of General Surgery and Institute of Precision Diagnosis and Treatment of Digestive System Tumors, Carson International Cancer Center, Shenzhen University General Hospital, Shenzhen University, Shenzhen 518055, Guangdong, China
  Medicine and Engineering Interdisciplinary Research Laboratory of Nursing and Materials, West China Hospital, Sichuan University, Chengdu 610041, China
  Institute of Biomedical Engineering, College of Medicine, Southwest Jiaotong University, Chengdu 610031, China
  Informatics Engineering Department, Faculty of Science and Technology, University of Coimbra, 3030-290 Coimbra, Portugal
- Author bio：
  
  *Paulo de Carvalho, carvalho@dei.uc.pt;
  Tao Tan, taotan@mpu.edu.mo;
  Ke-Feng Li, kefengl@mpu.edu.mo
- Funds：
  
  the Macao Polytechnic University(RP/FCA-14/2023);the Science and Technology Development Funds (FDCT) of Macao(0033/2023/RIB2);the Joint Research Funding Program between FDCT and the Department of Science and Technology of Guangdong Province (FDCT-GDST)(0009/2024/AGJ);the Joint Research Fund between FDCT and the Ministry of Science and Technology of China (FDCT-MOST)(0106/2025/AMJ);the Anusandhan National Research Foundation (ANRF) under the Partnerships for Accelerated Innovation and Research (PAIR) programme under the sanction order(ANRF/PAIR/2025/000029/PAIR)
- DOI：10.1016/j.mmr.2026.100050
  中图分类号：
- 收稿：2025-10-22，
  
  录用：2026-06-23，
  
  纸质出版：2026-06
- Accepted：
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Yu-Yang Sha, Li Yu, Ze-Hui Lin, 等. A roadmap for medical large language models: a review of foundations, applications, and challenges[J/OL]. 军事医学研究（英文）, 2026.

Sha YY, Yu L, Lin ZH, Kaur A, Lou YY, Gornale SS, et al. A roadmap for medical large language models: a review of foundations, applications, and challenges. Mil Med Res. 2026;13(1):100050.
Yu-Yang Sha, Li Yu, Ze-Hui Lin, 等. A roadmap for medical large language models: a review of foundations, applications, and challenges[J/OL]. 军事医学研究（英文）, 2026. DOI： 10.1016/j.mmr.2026.100050.

Sha YY, Yu L, Lin ZH, Kaur A, Lou YY, Gornale SS, et al. A roadmap for medical large language models: a review of foundations, applications, and challenges. Mil Med Res. 2026;13(1):100050. DOI： 10.1016/j.mmr.2026.100050.

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A roadmap for medical large language models: a review of foundations, applications, and challenges

A roadmap for medical large language models: a review of foundations, applications, and challenges

DOI：10.1016/j.mmr.2026.100050