Development of a prognostic prediction support system for cervical intraepithelial neoplasia using artificial intelligence-based diagnosis.

ABSTRACT:

Objective

Human papillomavirus subtypes are predictive indicators of cervical intraepithelial neoplasia (CIN) progression. While colposcopy is also an essential part of cervical cancer prevention, its accuracy and reproducibility are limited because of subjective evaluation. This study aimed to develop an artificial intelligence (AI) algorithm that can accurately detect the optimal lesion associated with prognosis using colposcopic images of CIN2 patients by utilizing objective AI diagnosis.

Methods

We identified colposcopic findings associated with the prognosis of patients with CIN2. We developed a convolutional neural network that can automatically detect the rate of high-grade lesions in the uterovaginal area in 12 segments. We finally evaluated the detection accuracy of

SUBMITTER: Takahashi T 

PROVIDER: S-EPMC9428307 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature