Melanoma Skin Cancer Detection with the Integration of a Conversational Chatbot
Bhagyashree Kadam1, Ritesh Kolhe2, Sagar Gonjare3, Rameshwar Shinde4, Sanket Yelam5
1Bhagyashree Kadam, Department of Information Technology, JSPM BSIOTR, Pune (Maharashtra), India.
2Ritesh Kolhe, Department of Information Technology, JSPM BSIOTR, Pune (Maharashtra), India.
3Sagar Gonjare, Department of Information Technology, JSPM BSIOTR, Pune (Maharashtra), India.
4Rameshwar Shinde, Department of Information Technology, JSPM BSIOTR, Pune (Maharashtra), India.
5Sanket Yelam, Department of Information Technology, JSPM BSIOTR, Pune (Maharashtra), India.
Manuscript received on 13 January 2025 | First Revised Manuscript received on 20 January 2025 | Second Revised Manuscript received on 25 February 2025 | Manuscript Accepted on 15 March 2025 | Manuscript published on 30 March 2025 | PP: 28-31 | Volume-5 Issue-3, March 2025 | Retrieval Number: 100.1/ijpmh.C105705030325 | DOI: 10.54105/ijpmh.C1057.05030325
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Skin cancer, specifically melanoma, results from abnormal melanocytic cell growth and can be fatal. It typically appears as dark lesions due to UV exposure and genetic factors. Early detection is crucial fortreatment. The conventional method, biopsy, is invasive, painful, and slow, as it requires lab analysis. To address these issues, a non- invasive computer-aided diagnosis (CAD) system is proposed, using dermoscopy images. This system preprocesses the images, segments the lesion, extracts unique features, and then classifies the skin as normal or cancerous using a support vector machine (SVM). The SVM with a linear kernel demonstrates optimal accuracy. CAD eliminates the need for physical contact, reducing pain and improving efficiency in melanoma detection through advanced image processing techniques.
Keywords: Skin Cancer, Melanoma, Feature Extraction, SVM, CAD, Image Processing, Dermoscopy.
Scope of the Article: Public Health