1. How Far Will Clinical Application of AI Applications Advance for Colorectal Cancer Diagnosis?
- Author
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Shin-ei Kudo, Kenichi Takeda, Kensaku Mori, Yuichi Mori, Masahiro Oda, Toyoki Kudo, Masashi Misawa, and Hayato Itoh
- Subjects
medicine.medical_specialty ,Invasive carcinoma ,medicine.diagnostic_test ,business.industry ,Research areas ,Colorectal cancer ,Colonoscopy ,colorectal cancer ,Review Article ,Lymph node metastasis ,medicine.disease ,digestive system diseases ,machine learning ,colonoscopy ,Computer-aided diagnosis ,medicine ,computer-aided diagnosis ,lcsh:Diseases of the digestive system. Gastroenterology ,Medical physics ,Applications of artificial intelligence ,lcsh:RC799-869 ,Colonoscopy procedures ,business - Abstract
Integrating artificial intelligence (AI) applications into colonoscopy practice is being accelerated as deep learning technologies emerge. In this field, most of the preceding research has focused on polyp detection and characterization, which can mitigate inherent human errors accompanying colonoscopy procedures. On the other hand, more challenging research areas are currently capturing attention: the automated prediction of invasive cancers. Colorectal cancers (CRCs) harbor potential lymph node metastasis when they invade deeply into submucosal layers, which should be resected surgically rather than endoscopically. However, pretreatment discrimination of deeply invasive submucosal CRCs is considered difficult, according to previous prospective studies (e.g.
- Published
- 2020
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