Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images

By T. Hirasawa, Kazuharu Aoyama, T. Tanimoto, S. Ishihara, S. Shichijo, Tsuyoshi Ozawa, T. Ohnishi, M. Fujishiro, K. Matsuo, J. Fujisaki and 1 more. Gastric Cancer, 2018

682 citations recorded by the source corpus.

Subfields: Gastroenterology, Oncology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/a76cf088961b65df2dfcd7494a15d40f6f9e75e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Lena Maier-Hein
2. Yuqi Guo
3. M. Eisenmann
4. Zhichao Hao
5. S. Vedula
6. Duygu Sarikaya
7. Gregory Hager
8. Pierre Jannin

Citations in the corpus

• Surgical data science – from concepts toward clinical translation (2020, background): “Endoscopic AI (AI Medical Service, Tokyo, Japan) and GI GeniusTM (Medtronic, Dublin, Ireland) support gastroenterologists in the detection of cancerous lesions, the former albeit struggling with a low positive predictive value (Hirasawa et al., 2018).”
• Artificial Intelligence in Health Care: Bibliometric Analysis (2020, background): “AI is making its way into cancer treatment from diagnostic classification to tumor behavior prediction [29,30].”