{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T05:32:09Z","timestamp":1793165529259,"version":"4.5.0"},"reference-count":55,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"Basic Science Research Program of the National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2023-00240521"],"award-info":[{"award-number":["RS-2023-00240521"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RISE Program of Gyeongsangbuk-do","award":["RS-2023-00240521"],"award-info":[{"award-number":["RS-2023-00240521"]}]},{"name":"RISE Program of Kumoh National Institute of Technology","award":["RS-2023-00240521"],"award-info":[{"award-number":["RS-2023-00240521"]}],"id":[{"id":"https:\/\/ror.org\/05dkjfz60","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objective: The global spread of Monkeypox (Mpox) has highlighted the urgent need for rapid, accurate diagnostic tools. Traditional methods like polymerase chain reaction (PCR) are resource-intensive, while skin image-based detection offers a promising alternative. This study evaluates the effectiveness of vision transformers (ViTs) for automated Mpox detection. Methods: By fine-tuning a pre-trained ViT model on an Mpox lesion image dataset, a robust ViT-based transfer learning (TL) model was created. Performance was assessed relative to convolutional neural network (CNN)-based TL models and ViT models trained from scratch across key metrics: accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). Furthermore, a transferability measure was utilized to assess the effectiveness of feature transfer to Mpox images. Results: The results show that the ViT model outperformed a CNN, achieving an AUC of 0.948 and an accuracy of 0.942 with a p-value of less than 0.05 across all metrics, highlighting its potential for accurate and scalable Mpox detection. Moreover, the ViT models yielded a better hypothesis margin-based transferability measure, highlighting its effectiveness in transferring useful learning weights to Mpox images. Gradient-weighted Class Activation Mapping (Grad-CAM) visualizations also confirmed that the ViT model attends to clinically relevant features, supporting its interpretability and reliability for diagnostic use. Conclusions: The results from this study suggest that ViT offers superior accuracy, making it a valuable tool for Mpox early detection in field settings, especially where conventional diagnostics are limited. This approach could support faster outbreak response and improved resource allocation in public health systems.<\/jats:p>","DOI":"10.3390\/diagnostics15131698","type":"journal-article","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T06:01:33Z","timestamp":1751522493000},"page":"1698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Breaking Diagnostic Barriers: Vision Transformers Redefine Monkeypox Detection"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5219-6098","authenticated-orcid":false,"given":"Gelan","family":"Ayana","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Kumoh National Institute of Technology, Gumi 39253, Republic of Korea"},{"name":"School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma 378, Ethiopia"},{"name":"Artificial Intelligence & Mathematical Modeling Lab (AIMM Lab), Dalla Lana School of Public Health, University of Toronto, 155 College St Room 500, Toronto, ON M5T 3M7, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2449-8491","authenticated-orcid":false,"given":"Beshatu Debela","family":"Wako","sequence":"additional","affiliation":[{"name":"Center of Biomedical Engineering, Jimma University Medical Center, Jimma 378, Ethiopia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4411-1277","authenticated-orcid":false,"given":"So-yun","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Kumoh National Institute of Technology, Gumi 39253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7557-5672","authenticated-orcid":false,"given":"Jude","family":"Kong","sequence":"additional","affiliation":[{"name":"Artificial Intelligence & Mathematical Modeling Lab (AIMM Lab), Dalla Lana School of Public Health, University of Toronto, 155 College St Room 500, Toronto, ON M5T 3M7, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sahng Min","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Gwinnett Technical College, Lawrenceville, GA 30043, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soon-Do","family":"Yoon","sequence":"additional","affiliation":[{"name":"Department of Chemical and Biomolecular Engineering, Chonnam National University, Yeosu 59626, Republic of Korea"},{"name":"Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7298-4147","authenticated-orcid":false,"given":"Se-woon","family":"Choe","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Kumoh National Institute of Technology, Gumi 39253, Republic of Korea"},{"name":"Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100141","DOI":"10.1016\/j.microb.2024.100141","article-title":"Unveiling the Global Surge of Mpox (Monkeypox): A comprehensive review of current evidence","volume":"4","author":"Duarte","year":"2024","journal-title":"Microbe"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1038\/s41392-023-01675-2","article-title":"Mpox (formerly monkeypox): Pathogenesis, prevention, and treatment","volume":"8","author":"Lu","year":"2023","journal-title":"Signal Transduct. 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