Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies.

ABSTRACT:

Background

Colposcopy diagnosis and directed biopsy are the key components in cervical cancer screening programs. However, their performance is limited by the requirement for experienced colposcopists. This study aimed to develop and validate a Colposcopic Artificial Intelligence Auxiliary Diagnostic System (CAIADS) for grading colposcopic impressions and guiding biopsies.

Methods

Anonymized digital records of 19,435 patients were obtained from six hospitals across China. These records included colposcopic images, clinical information, and pathological results (gold standard). The data were randomly assigned (7:1:2) to a training and a tuning set for developing CAIADS and to a validation set for evaluating performance.

Results

The agreement between CAIADS-graded colpo

SUBMITTER: Xue P 

PROVIDER: S-EPMC7754595 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature