Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media.

ABSTRACT: Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease st

SUBMITTER: Schaumberg AJ 

PROVIDER: S-EPMC7581495 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature