{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T04:27:22Z","timestamp":1786422442462,"version":"build-2736575974"},"reference-count":63,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T00:00:00Z","timestamp":1668988800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004242","name":"Princess Nourah bint Abdulrahman University","doi-asserted-by":"publisher","award":["PNURSP2022R300"],"award-info":[{"award-number":["PNURSP2022R300"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Human skin diseases have become increasingly prevalent in recent decades, with millions of individuals in developed countries experiencing monkeypox. Such conditions often carry less obvious but no less devastating risks, including increased vulnerability to monkeypox, cancer, and low self-esteem. Due to the low visual resolution of monkeypox disease images, medical specialists with high-level tools are typically required for a proper diagnosis. The manual diagnosis of monkeypox disease is subjective, time-consuming, and labor-intensive. Therefore, it is necessary to create a computer-aided approach for the automated diagnosis of monkeypox disease. Most research articles on monkeypox disease relied on convolutional neural networks (CNNs) and using classical loss functions, allowing them to pick up discriminative elements in monkeypox images. To enhance this, a novel framework using Al-Biruni Earth radius (BER) optimization-based stochastic fractal search (BERSFS) is proposed to fine-tune the deep CNN layers for classifying monkeypox disease from images. As a first step in the proposed approach, we use deep CNN-based models to learn the embedding of input images in Euclidean space. In the second step, we use an optimized classification model based on the triplet loss function to calculate the distance between pairs of images in Euclidean space and learn features that may be used to distinguish between different cases, including monkeypox cases. The proposed approach uses images of human skin diseases obtained from an African hospital. The experimental results of the study demonstrate the proposed framework\u2019s efficacy, as it outperforms numerous examples of prior research on skin disease problems. On the other hand, statistical experiments with Wilcoxon and analysis of variance (ANOVA) tests are conducted to evaluate the proposed approach in terms of effectiveness and stability. The recorded results confirm the superiority of the proposed method when compared with other optimization algorithms and machine learning models.<\/jats:p>","DOI":"10.3390\/diagnostics12112892","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T03:04:20Z","timestamp":1669086260000},"page":"2892","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":91,"title":["An Al-Biruni Earth Radius Optimization-Based Deep Convolutional Neural Network for Classifying Monkeypox Disease"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9843-6392","authenticated-orcid":false,"given":"Doaa Sami","family":"Khafaga","sequence":"first","affiliation":[{"name":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8352-6731","authenticated-orcid":false,"given":"Abdelhameed","family":"Ibrahim","sequence":"additional","affiliation":[{"name":"Computer Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9221-7658","authenticated-orcid":false,"given":"El-Sayed M.","family":"El-Kenawy","sequence":"additional","affiliation":[{"name":"Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7080-1979","authenticated-orcid":false,"given":"Abdelaziz A.","family":"Abdelhamid","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra 11961, Saudi Arabia"},{"name":"Department of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Faten Khalid","family":"Karim","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1443-9458","authenticated-orcid":false,"given":"Seyedali","family":"Mirjalili","sequence":"additional","affiliation":[{"name":"Centre for Artificial Intelligence Research and Optimization, Torrens University Australia, Fortitude Valley, QLD 4006, Australia"},{"name":"Yonsei Frontier Lab, Yonsei University, Seoul 03722, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8348-6530","authenticated-orcid":false,"given":"Nima","family":"Khodadadi","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Florida International University, Miami, FL 33199, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1673-8088","authenticated-orcid":false,"given":"Wei Hong","family":"Lim","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur 56000, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8557-3566","authenticated-orcid":false,"given":"Marwa M.","family":"Eid","sequence":"additional","affiliation":[{"name":"Faculty of Artificial Intelligence, Delta University for Science and Technology, Mansoura 35712, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0335-4686","authenticated-orcid":false,"given":"Mohamed E.","family":"Ghoneim","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences, Faculty of Applied Science, Umm Al-Qura University, Makkah 21955, Saudi Arabia"},{"name":"Faculty of Computers and Artificial Intelligence, Damietta University, Damietta 34511, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Somogyi, Z. 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