Development of an artificial intelligence-based multimodal diagnostic system for early detection of biliary atresia.

Journal: BMC medicine
PMID: 40016769

Abstract

BACKGROUND: Early diagnosis of biliary atresia (BA) is crucial for improving patient outcomes, yet remains a significant global challenge. This challenge may be ameliorated through the application of artificial intelligence (AI). Despite the promise of AI in medical diagnostics, its application to multimodal BA data has not yet achieved substantial breakthroughs. This study aims to leverage diverse data sources and formats to develop an intelligent diagnostic system for BA.

Authors

  • Ya Ma
    School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510641, People's Republic of China.
  • Yuancheng Yang
    School of Computer Science and Engineering, Beihang University, Beijing, China.
  • Yuxin Du
    School of Computer Science and Engineering, Beihang University, Beijing, China.
  • Luyang Jin
    School of Computer Science and Engineering, Beihang University, Beijing, China.
  • Baoyu Liang
    School of Computer Science and Engineering, Beihang, Beijing, 100191, China.
  • Yuqi Zhang
    State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing, China.
  • Yedi Wang
    Department of Ultrasound, Capital Institute of Pediatrics, Beijing, China.
  • Luyu Liu
    Department of Dermatology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Zijian Zhang
    School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Zelong Jin
    Department of Ultrasound, Capital Institute of Pediatrics, Beijing, China.
  • Zhimin Qiu
    Department of Ultrasound, Capital Institute of Pediatrics, Beijing, China.
  • Mao Ye
    Department of General Surgery, Capital Institute of Pediatrics, Beijing, China.
  • Zhengrong Wang
    Department of Ultrasound, Capital Institute of Pediatrics, Beijing, China. wenzcip@163.com.
  • Chao Tong
    School of Computer Science and Engineering, Beihang, Beijing, 100191, China.

Keywords

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