No-Code Platform-Based Deep-Learning Models for Prediction of Colorectal Polyp Histology from White-Light Endoscopy Images: Development and Performance Verification

Background: The authors previously developed deep-learning models for the prediction of colorectal polyp histology (advanced colorectal cancer, early cancer/high-grade dysplasia, tubular adenoma with or without low-grade dysplasia, or non-neoplasm) from endoscopic images. While the model achieved 67...

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Veröffentlicht in:	Journal of personalized medicine 2022-06, Vol.12 (6), p.963
Hauptverfasser:	Gong, Eun Jeong, Bang, Chang Seok, Lee, Jae Jun, Seo, Seung In, Yang, Young Joo, Baik, Gwang Ho, Kim, Jong Wook
Format:	Artikel
Sprache:	eng
Schlagworte:	Adenoma Colorectal carcinoma Datasets Dysplasia Endoscopy Learning Neural networks Polyps Precision medicine Predictions Software
Online-Zugang:	Volltext
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