Diagnosing Solid Lesions in the Pancreas With Multimodal Artificial Intelligence: A Randomized Crossover Trial.

Journal: JAMA network open
PMID: 39028670

Abstract

IMPORTANCE: Diagnosing solid lesions in the pancreas via endoscopic ultrasonographic (EUS) images is challenging. Artificial intelligence (AI) has the potential to help with such diagnosis, but existing AI models focus solely on a single modality.

Authors

  • Haochen Cui
    Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yuchong Zhao
    Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Si Xiong
    Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Yunlu Feng
    Department of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Peng Li
    WuXi AppTec Co, Shanghai, China.
  • Ying Lv
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Qian Chen
    Department of Pain Medicine Guizhou Provincial Orthopedics Hospital Guiyang Guizhou China.
  • Ronghua Wang
    Shenzhen Polytechnic, Shenzhen 518055, China.
  • Pengtao Xie
    Department of Electrical and Computer Engineering, University of California San Diego, San Diego, USA. p1xie@eng.ucsd.edu.
  • Zhenlong Luo
    Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Sideng Cheng
    Department of Computer Science, Algoma University, Sault Ste. Marie, Ontario, Canada.
  • Wujun Wang
    Wuhan EndoAngel Medical Technology Co., Ltd., Wuhan, China.
  • Xing Li
    Department of Nutrition and food hygiene, College of Public Health of Zhengzhou University, Zhengzhou, China, 450001. Electronic address: 526924683@qq.com.
  • Dingkun Xiong
    Department of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Xinyuan Cao
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China.
  • Shuya Bai
    Department of Gastroenterology and Hepatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Aiming Yang
    Department of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
  • Bin Cheng

Keywords

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