Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Role of Artificial Intelligence Interpretation of Colposcopic Images in Cervical Cancer Screening

Authors
Kim, SeongminLee, HwajungLee, SanghoonSong, Jae-YunLee, Jae-KwanLee, Nak-Woo
Issue Date
3월-2022
Publisher
MDPI
Keywords
artificial intelligence; cervical cancer screening; colposcopy; deep learning; machine learning
Citation
HEALTHCARE, v.10, no.3
Indexed
SCIE
SSCI
SCOPUS
Journal Title
HEALTHCARE
Volume
10
Number
3
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/140452
DOI
10.3390/healthcare10030468
ISSN
2227-9032
Abstract
The accuracy of colposcopic diagnosis depends on the skill and proficiency of physicians. This study evaluated the feasibility of interpreting colposcopic images with the assistance of artificial intelligence (AI) for the diagnosis of high-grade cervical intraepithelial lesions. This study included female patients who underwent colposcopy-guided biopsy in 2020 at two institutions in the Republic of Korea. Two experienced colposcopists reviewed all images separately. The Cerviray AI (R) system (AIDOT, Seoul, Korea) was used to interpret the cervical images. AI demonstrated improved sensitivity with comparable specificity and positive predictive value when compared with the colposcopic impressions of each clinician. The areas under the curve were greater with combined impressions (both AI and that of the two colposcopists) of high-grade lesions, when compared with the individual impressions of each colposcopist. This study highlights the feasibility of the application of an AI system in cervical cancer screening. AI interpretation can be utilized as an assisting tool in combination with human colposcopic evaluation of exocervix.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Medicine > Department of Medical Science > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Jae Kwan photo

Lee, Jae Kwan
의과대학 (의학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE