Improved Detection of Dermatological Conditions with AI-Based Models
Year: 2025
Type: article
Abstract: This paper presents a machine learning-based framework for enhancing the accuracy of early skin disease detection and classification. The proposed approach involves a hybrid model combining Principal Component Analysis (PCA) for dimensionality reduction and Naive Bayes for classification. Various supervised algorithms, including Support Vector Machines (SVM), Decision Trees, K-Nearest Neighbors (KNN), and ensemble models, are also evaluated. Results show that the hybrid model outperforms other methods in accuracy and efficiency, offering promising support for dermatological diagnostics.
Authors: Subraja T, Dr. M Marikkannan
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6912002957
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