{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T01:45:26Z","timestamp":1774921526652,"version":"3.50.1"},"reference-count":26,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T00:00:00Z","timestamp":1763164800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Biophotonics"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Vulvar intraepithelial neoplasia (VIN) is increasing in prevalence, yet screening options remain limited and existing diagnostic methods show low accuracy. This study evaluates infrared thermal imaging as an alternative screening approach for VIN detection. We analyzed thermal images from 51 patients with histopathologically confirmed VIN, captured using a FLIR A400 thermal camera. Temperature distributions of healthy vulvar tissue were first characterized to establish baseline values. Thermal features of VIN lesions were then extracted and optimized using principal component analysis (PCA). Three machine learning models\u2014support vector machine (SVM), random forest (RF), and linear discriminant analysis (LDA)\u2014were trained and evaluated for VIN diagnosis. SVM demonstrated the best performance with an\n                    <jats:italic>F<\/jats:italic>\n                    1 score of 75% and accuracy of 74.19%. These findings suggest that machine learning\u2010based infrared thermography shows promise as a non\u2010invasive screening tool for VIN detection.\n                  <\/jats:p>","DOI":"10.1002\/jbio.202500157","type":"journal-article","created":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:53:11Z","timestamp":1763203991000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning\u2010Based Thermal Imaging for Vulvar Intraepithelial Neoplasia Detection"],"prefix":"10.1002","volume":"19","author":[{"given":"Haonan","family":"Zeng","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shupei","family":"Qiao","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering City University of Hong Kong Hong Kong China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuerui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maoyu","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingjie","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence Anhui Polytechnic University Wuhu Anhui China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4381-9104","authenticated-orcid":false,"given":"Shufang","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology The Second Affiliated Hospital of Chongqing Medical University Chongqing China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,11,15]]},"reference":[{"issue":"3","key":"e_1_2_9_2_1","first-page":"217","article-title":"Propozycje Podzia\u0142u i Mianownictwa Schorze\u0144 Sromu [Classification and Nomenclature of Vulvar Diseases]","volume":"52","author":"Miecznikowski A.","year":"1981","journal-title":"Ginekologia Polska"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.33198"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers14071822"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ogc.2017.04.003"},{"issue":"3","key":"e_1_2_9_6_1","first-page":"179","article-title":"Vulvar Pruritus: Determination of the Most Common Causes and Their Treatments","volume":"83","author":"Carrillo\u2010Mel\u00e9ndrez H.","year":"2015","journal-title":"Ginecolog\u00eda y Obstetricia de M\u00e9xico"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygyno.2020.02.026"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.AOG.0000187301.76283.7f"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpobgyn.2014.07.010"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00404\u2010015\u20103666\u20105"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.15406\/ogij.2020.11.00531"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1097\/LGT.0b013e31819308d4"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.21873\/cgp.20175"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pathol.2016.02.015"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jogoh.2020.101801"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/his.15050"},{"key":"e_1_2_9_17_1","first-page":"1306","article-title":"New Machine\u2010Learning Technologies for Computer\u2010Aided Diagnosis","volume":"24","author":"Liston C. 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