From labels to priors in capsule endoscopy: a prior guided approach for improving generalization with few labels.

ABSTRACT: The lack of generalizability of deep learning approaches for the automated diagnosis of pathologies in Wireless Capsule Endoscopy (WCE) has prevented any significant advantages from trickling down to real clinical practices. As a result, disease management using WCE continues to depend on exhaustive manual investigations by medical experts. This explains its limited use despite several advantages. Prior works have considered using higher quality and quantity of labels as a way of tackling the lack of generalization, however this is hardly scalable considering pathology diversity not to mention that labeling large datasets encumbers the medical staff additionally. We propose using freely available domain knowledge as priors to learn more robust and generalizable representations. We experime

SUBMITTER: Vats A 

PROVIDER: S-EPMC9489743 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature