| Literature DB >> 34252041 |
Anant Madabhushi1,2, Paula Toro3, Joseph E Willis4,5.
Abstract
A study by Waterhouse and colleagues in a previous issue of Cancer Research describes the development and prospective validation of an artificial intelligence approach in conjunction with spectral imaging to enhance endoscopic detection of Barrett's esophagus-related neoplasia. The authors developed a novel spectral endoscope with external optics suitable for routine Barrett's esophagus surveillance with diffuse tissue reflectance to define multispectral data correlated with histopathology. A convolutional neural network was trained on the absis of the spectral signatures acquired as part of a small, prospective clinical trial to distinguish Barrett's esophagus from Barrett's esophagus neoplasia. The results from the study suggest the utility of artificial intelligence for diagnosis of Barrett's esophagus.See related article by Waterhouse et al., Cancer Res 2021;81:3415-25. ©2021 American Association for Cancer Research.Entities:
Mesh:
Year: 2021 PMID: 34252041 PMCID: PMC9494280 DOI: 10.1158/0008-5472.CAN-21-1511
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 13.312