What question did this study set out to answer?

To develop a predictive system for early skin cancer detection and accurate classification of skin lesions.

February 27, 20260 citationsOpen Access

Skin Cancer Prediction

DMDr. Rajesh Kannan V, Mr. Ilanthirayan R, Mr. Siva Kumar S, Mr. Guna Chandru M

Key Points

To develop a predictive system for early skin cancer detection and accurate classification of skin lesions.
Utilized a convolutional neural network for classification tasks.
Applied transfer learning techniques to improve model accuracy.
Incorporated user-friendly interfaces for providing diagnostic feedback.
Executed preprocessing on dermoscopic skin images for analysis.
Achieved high classification accuracy in skin lesion identification.
Demonstrated effectiveness in real-world healthcare applications.
Reduced reliance on dermatologists for initial screening and diagnosis.

Abstract

Abstract—Skin cancer is one of the most common and rapidlyincreasing forms of cancer worldwide, and early detection iscritical for improving survival rates and treatment outcomes.SkinScan is an intelligent skin cancer prediction systemthat assistance to support early diagnosis in real time. Thesystem captures dermoscopic skin images, performspreprocessing, and classifies skin lessions using a convolutionneural network(CNN) based on transfer learning techniques.SkinScan also provides user-friendly diagnostic feedback,precautionary guidance, and an AI-powered medical chatbot,making it accessible to users with varying levels of medicalknowledge.The proposed system enables fast and accurate skin lesionclassification, reducing dependency on dermatologists forinitial screening and minimizing delays in diagnosis. Byoffering clear risk assessment and preventiverecommendations, SkinScan assists users in taking timelymedical actions and seeking professional care when necessary.Experimental results demonstrate high classification accuracy,validating the effectiveness and reliability of the proposedsystem in real-world healthcare scenarios. The systemsupports early cancer detection and promotes preventivehealthcare by combining advanced deep learning models withan intuitive and patient- centered design

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