Role of Artificial Intelligence Interpretation of Colposcopic Images in Cervical Cancer Screening
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Seongmin | - |
dc.contributor.author | Lee, Hwajung | - |
dc.contributor.author | Lee, Sanghoon | - |
dc.contributor.author | Song, Jae-Yun | - |
dc.contributor.author | Lee, Jae-Kwan | - |
dc.contributor.author | Lee, Nak-Woo | - |
dc.date.accessioned | 2022-04-28T14:40:52Z | - |
dc.date.available | 2022-04-28T14:40:52Z | - |
dc.date.created | 2022-04-28 | - |
dc.date.issued | 2022-03 | - |
dc.identifier.issn | 2227-9032 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/140452 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | INTRAEPITHELIAL NEOPLASIA | - |
dc.subject | CYTOLOGY | - |
dc.subject | CLASSIFICATION | - |
dc.subject | REGRESSION | - |
dc.subject | DIAGNOSIS | - |
dc.subject | SMEAR | - |
dc.title | Role of Artificial Intelligence Interpretation of Colposcopic Images in Cervical Cancer Screening | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Jae-Kwan | - |
dc.identifier.doi | 10.3390/healthcare10030468 | - |
dc.identifier.scopusid | 2-s2.0-85125940469 | - |
dc.identifier.wosid | 000775307100001 | - |
dc.identifier.bibliographicCitation | HEALTHCARE, v.10, no.3 | - |
dc.relation.isPartOf | HEALTHCARE | - |
dc.citation.title | HEALTHCARE | - |
dc.citation.volume | 10 | - |
dc.citation.number | 3 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Health Care Sciences & Services | - |
dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services | - |
dc.relation.journalWebOfScienceCategory | Health Policy & Services | - |
dc.subject.keywordPlus | INTRAEPITHELIAL NEOPLASIA | - |
dc.subject.keywordPlus | CYTOLOGY | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | REGRESSION | - |
dc.subject.keywordPlus | DIAGNOSIS | - |
dc.subject.keywordPlus | SMEAR | - |
dc.subject.keywordAuthor | artificial intelligence | - |
dc.subject.keywordAuthor | cervical cancer screening | - |
dc.subject.keywordAuthor | colposcopy | - |
dc.subject.keywordAuthor | deep learning | - |
dc.subject.keywordAuthor | machine learning | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.