{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:50:51Z","timestamp":1767340251442,"version":"3.40.5"},"reference-count":9,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Dermatology"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Palmoplantar pustulosis (PPP) is a variant of pustular psoriasis involving the palms and soles. The severity of PPP is usually evaluated using the Palmoplantar Pustulosis Area and Severity Index (PPPASI). Among the components of the PPPASI, the area of the involved lesion is evaluated differently by raters, who generally make a rough estimate using the eye and not through a specific calculation. To overcome inconsistent evaluation of the area subscore of PPPASI by human raters, we developed and validated deep\u2010learning\u2010based algorithms to enable automated and reliable assessment of the area involved in PPP to provide clinical advantages. In this study, we developed a dataset of 611 images of the palms and soles of 153 patients with PPP. We evaluated the area of the lesion by dividing the number of pixels in the area involved in PPP by the number of pixels in the area of the palms or soles. Using attention U\u2010net, we developed\u00a0two convolutional neural network (CNN) models that can evaluate the percentage of the affected area (%) and subsequently assign a score ranging from 0 to 6. The area subscore of PPPASI evaluated by the deep\u2010learning algorithm\u00a0was\u00a0same\u00a0or differed by 1\u2010point from the subscore of ground truth in 98.8% of the images. The intraclass correlation coefficient between the CNN and ground truth was 0.879, indicating good agreement. The accuracy and mean absolute error of the model were 66.7% and 0.344, respectively. In a Bland\u2013Altman plot, most of the differences in the percentage of the affected area lay between the 95% confidence interval with a mean difference of 0 and a standard deviation of 0.2. The deep\u2010learning algorithm can provide several clinical advantages by objectively evaluating the components of the PPPASI without concern for disagreement between clinicians. The algorithms further enable cumulative clinical data acquisition related to PPP severity.<\/jats:p>","DOI":"10.1111\/1346-8138.16752","type":"journal-article","created":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T08:56:56Z","timestamp":1677142616000},"page":"787-792","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation of the area subscore of the Palmoplantar Pustulosis Area and Severity Index using an attention U\u2010net deep learning algorithm"],"prefix":"10.1111","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5706-2371","authenticated-orcid":false,"given":"Kyungho","family":"Paik","sequence":"first","affiliation":[{"name":"Department of Dermatology Seoul National University Bundang Hospital  Seongnam South Korea"},{"name":"Department of Dermatology Seoul National University College of Medicine  Seoul South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2223-1606","authenticated-orcid":false,"given":"Bo Ri","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Dermatology Seoul National University Bundang Hospital  Seongnam South Korea"},{"name":"Department of Dermatology Seoul National University College of Medicine  Seoul South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5602-3530","authenticated-orcid":false,"given":"Sang Woong","family":"Youn","sequence":"additional","affiliation":[{"name":"Department of Dermatology Seoul National University Bundang Hospital  Seongnam South Korea"},{"name":"Department of Dermatology Seoul National University College of Medicine  Seoul South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.2147\/CCID.S240607"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/bjd.12223"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2014-006450"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_7_6_1","unstructured":"OktayO SchlemperJ Le FolgocL et al.Attention U\u2010net: learning where to look for the pancreas.Arxiv e\u2010Prints.2018: Available at: arXiv:1804.03999."},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcm.2016.02.012"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1590\/S0365-05962010000500005"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/ckj\/sfaa188"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1111\/jdv.17711"}],"container-title":["The Journal of Dermatology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/1346-8138.16752","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/1346-8138.16752","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/1346-8138.16752","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,20]],"date-time":"2023-08-20T09:38:41Z","timestamp":1692524321000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/1346-8138.16752"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,23]]},"references-count":9,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["10.1111\/1346-8138.16752"],"URL":"https:\/\/doi.org\/10.1111\/1346-8138.16752","archive":["Portico"],"relation":{},"ISSN":["0385-2407","1346-8138"],"issn-type":[{"type":"print","value":"0385-2407"},{"type":"electronic","value":"1346-8138"}],"subject":[],"published":{"date-parts":[[2023,2,23]]},"assertion":[{"value":"2022-12-04","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-02-03","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-02-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}