Diagnostic performance of endoscopic ultrasound-artificial intelligence using deep learning analysis of gallbladder polypoid lesions.

Journal: Journal of gastroenterology and hepatology
Published Date: Dec 1, 2021

Abstract

BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most accurate diagnostic modality for polypoid lesions of the gallbladder (GB), but is limited by subjective interpretation. Deep learning-based artificial intelligence (AI) algorithms are under development. We evaluated the diagnostic performance of AI in differentiating polypoid lesions using EUS images.

Authors

  • Sung Ill Jang
    Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Young Jae Kim
    Department of Biomedical Engineering, College of Medicine, Gachon University, Gyeonggi-do, Republic of Korea.
  • Eui Joo Kim
    Division of Gastroenterology, Department of Internal Medicine, Gachon University Gil Medcal Center, Gachon University College of Medicine, Incheon, Republic of Korea.
  • Huapyong Kang
    Department of Internal Medicine, Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea.
  • Seung Jin Shon
    Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Yu Jin Seol
    Department of Biomedical Engineering, Gachon University College of Health Science, Incheon, South Korea.
  • Dong Ki Lee
    Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Kwang Gi Kim
    Department of Biomedical Engineering Branch, National Cancer Center, Gyeonggi-do, South Korea.
  • Jae Hee Cho
    Division of Gastroenterology, Department of Internal Medicine, Gachon University Gil Medcal Center, Gachon University College of Medicine, Incheon, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals