Comparative Analysis of Automated Melanoma Recognition Algorithms in Dermoscopy

Author(s)	Mr. Mohd Muthi ur Rahman, Mr. M A Majed, Dr. Syeda Gauhar Fatima
Country	India
Abstract	This paper presents a comparative analysis of automated melanoma recognition algorithms in dermoscopy, highlighting the strengths and limitations of various state-of-the-art techniques. The study evaluates different image processing and machine learning approaches used for early melanoma detection, focusing on accuracy, sensitivity, specificity, and computational efficiency. Publicly available dermoscopic image datasets were utilized to ensure consistency in performance assessment. The results emphasize the critical role of data quality, algorithmic architecture, and preprocessing techniques in determining diagnostic performance. This analysis aims to guide future research toward more robust, interpretable, and clinically viable melanoma detection systems.
Keywords	melanoma detection, dermoscopy, image analysis, machine learning, algorithm comparison, computer-aided diagnosis
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-09-25

About IJSAT Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijsat.org

International Journal on Science and Technology