Skin Lesion Classification and Detection Using Machine Learning in Dermatology

Skin Lesion Classification and Detection Using Machine Learning in Dermatology | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Skin Lesion Classification and Detection Using Machine Learning in Dermatology Ashish Tripathi, Yara Mohammed Alshehri, Pradeep Kumar Arya, Rajnesh Singh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5976118/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract Skin diseases, also known as dermatological conditions, are conditions that affect the skin. Factors such as changing lifestyles, environmental pollution, increased stress levels, and inadequate access to healthcare in certain regions can contribute to the growing incidence of skin disorders. The traditional approach of diagnosing skin disease may not always provide accurate results, and the process would be very time-consuming and costly and is not even feasible in multiple regions. The proposed model will assist and ensure an accurate diagnosis of the patient's skin condition. In the proposed method, different algorithms (ANN, CNN, SVM, RF) are implemented and stacked in search of achieving more accurate result. The model is trained in such a manner that the diagnosis can be done based on the visual inputs given by the patients. The model is developed and trained to diagnose and classify multiple skin diseases. The datasets used contain images for training and testing purposes. The results generated by all the models used depend on how well the model is trained. ANN CNN RF SVM Skin Disease Melanoma Dermatofibroma Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 23 Apr, 2025 Reviews received at journal 23 Apr, 2025 Reviews received at journal 18 Apr, 2025 Reviews received at journal 31 Mar, 2025 Reviewers agreed at journal 26 Mar, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviewers agreed at journal 12 Mar, 2025 Reviewers invited by journal 11 Mar, 2025 Editor assigned by journal 11 Mar, 2025 Submission checks completed at journal 11 Feb, 2025 First submitted to journal 06 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5976118","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":414238593,"identity":"5a879c77-d886-4d10-9498-372341f52714","order_by":0,"name":"Ashish Tripathi","email":"","orcid":"","institution":"Galgotias University","correspondingAuthor":false,"prefix":"","firstName":"Ashish","middleName":"","lastName":"Tripathi","suffix":""},{"id":414238594,"identity":"8c58f110-d9d6-41b0-9402-569faecf4ff1","order_by":1,"name":"Yara Mohammed Alshehri","email":"","orcid":"","institution":"Imaam Mohammed Ibn Saud Islamic 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