AI System Beats Endoscopists for Detecting Early Neoplasia in Barrett's
One of the top publications in gastroenterology in 2020 was a Dutch study demonstrating that a computer-aided system suitable for real-time use in clinical practice detected early neoplasia in patients with Barrett's esophagus with impressively greater accuracy than did a group of general endoscopists. The deep-learning system developed, evaluated, and externally validated by the Dutch investigators is designed to reduce the rate of failed detection of high-grade dysplasia and early adenocarcinoma in patients undergoing surveillance by general practice gastrointestinal endoscopists. The false-negative rate in looking for the sometimes subtle mucosal surface abnormalities indicative of early neoplasia is known to be higher among these general endoscopists than that among expert endoscopists, and yet it's the general endoscopists who perform the majority of cancer surveillance in patients with Barrett's esophagus.
@rajan The deep-learning system had 93% sensitivity and 83% specificity for identification of early neoplasia, significantly better than the 72% sensitivity and 74% specificity for the general endoscopists. The overall accuracy of the computer-assisted detection system was 88%, compared to 73% for the general endoscopists. Moreover, the deep-learning system achieved greater accuracy than did any single one of the endoscopists.