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Deep Learning and Gastric Cancer: Systematic Review of AI-Assisted Endoscopy.

Eyal KlangAli SouroshGirish N NadkarniDennis McGonagleAdi Lahat
Published in: Diagnostics (Basel, Switzerland) (2023)
The promise of artificial intelligence in improving and standardizing gastric neoplasia detection, diagnosis, and segmentation is significant. This review is limited by predominantly single-center studies and undisclosed datasets used in AI training, impacting generalizability and demographic representation. Further, retrospective algorithm training may not reflect actual clinical performance, and a lack of model details hinders replication efforts. More research is needed to substantiate these findings, including larger-scale multi-center studies, prospective clinical trials, and comprehensive technical reporting of DL algorithms and datasets, particularly regarding the heterogeneity in DL algorithms and study designs.
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