Deep learning analysis for differential diagnosis and risk classification of gastrointestinal tumors

Author:

Iwai Tomohisa1,Kida Mitsuhiro1,Okuwaki Kosuke1,Watanabe Masafumi1,Adachi Kai1,Ishizaki Junro1,Hanaoka Taro1,Tamaki Akihiro1,Tadehara Masayoshi1,Imaizumi Hiroshi1,Kusano Chika1

Affiliation:

1. Department of Gastroenterology, Kitasato University School of Medicine, Sagamihara, Japan

Publisher

Informa UK Limited

Reference26 articles.

1. Gastrointestinal Stromal Tumors: Current Diagnosis, Biologic Behavior, and Management

2. Krizhevsky A, Sutskever I, Hinton GE. NIPS’12. Proceedings of the 25th International Conference on Neural Information Processing Systems; Lake Tahoe ImageNet Classification with Deep Convolutional Neural Networks; Communications of the ACM; 2012 Dec 3–6; NV. p. 1097–105.

3. Going deeper with convolutions

4. Artificial Intelligence and Deep Learning for Upper Gastrointestinal Neoplasia

5. Artificial Intelligence in Endoscopy

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1. Anatomical Benchmarks in the Training of Gastroenterologists;Journal of Gastrointestinal and Liver Diseases;2024-08-09

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