Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution.

Journal: Singapore medical journal
PMID: 38527297

Abstract

INTRODUCTION: Deep learning models can assess the quality of images and discriminate among abnormalities in small bowel capsule endoscopy (CE), reducing fatigue and the time needed for diagnosis. They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities.

Authors

  • Bochao Jiang
    Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore.
  • Michael Dorosan
    Health Services Research Centre, Singapore Health Services Pte Ltd, Singapore.
  • Justin Wen Hao Leong
    Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore.
  • Marcus Eng Hock Ong
    Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore. marcus.ong.e.h@sgh.com.sg.
  • Sean Shao Wei Lam
    Health Services Research Centre, Singapore Health Services Pte Ltd, Singapore.
  • Tiing Leong Ang
    Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore.

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