Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors

Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors

Background Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS images. If artificial intelligence (AI) can be use...

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Veröffentlicht in:Journal of gastroenterology 2020-12, Vol.55 (12), p.1119-1126
Hauptverfasser: Minoda, Yosuke, Ihara, Eikichi, Komori, Keishi, Ogino, Haruei, Otsuka, Yoshihiro, Chinen, Takatoshi, Tsuda, Yasuo, Ando, Koji, Yamamoto, Hidetaka, Ogawa, Yoshihiro
Format: Artikel
Sprache:eng
Schlagworte:
Abdominal Surgery
Artificial intelligence
Colorectal Surgery
Deep learning
Diagnosis
Endoscopic ultrasonography
Endoscopy
Gastroenterology
Gastrointestinal cancer
Hepatology
Medical diagnosis
Medicine
Medicine & Public Health
Original Article―Alimentary Tract
Surgical Oncology
Tumors
Ultrasonic imaging
Ultrasound
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Zusammenfassung:Background Although endoscopic ultrasound (EUS) is reported to be suitable for determining the layer from which subepithelial lesions (SELs) originate, it is difficult to distinguish gastrointestinal stromal tumor (GIST) from non-GIST using only EUS images. If artificial intelligence (AI) can be used for the diagnosis of SELs, it should provide several benefits, including objectivity, simplicity, and quickness. In this pilot study, we propose an AI diagnostic system for SELs and evaluate its efficacy. Methods Thirty sets each of EUS images with SELs ≥ 20 mm or
ISSN:0944-1174
1435-5922
DOI:10.1007/s00535-020-01725-4