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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
ISSN Online 2393-8021ISSN Print 2394-1588Since 2014
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← Back to VOLUME 13, ISSUE 2, FEBRUARY 2026

A Comparative Analysis of Machine Learning Models and Data Sources towards Effective Skin Disease Prediction

Kavyashree G J, Kavyashree Nagarajaiah

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Abstract: The human body consists of several organs and skin is the largest organ that covers human body. Any disorder that affects skin is known as skin disease. The main causes of skin lesion are bacteria, virus, fungal infections and some genetic factors. The accurate diagnosis of skin conditions is crucial for effective treatment and management. Dermatologist rely heavily on visual inspection and physical examination to identify and differentiate between various skin disease. This paper is highlighting frequently used datasets and figuring out the gaps, listing out existing machine learning algorithms and their accuracy. This paper gives the clear view of many algorithms' efficiency and limitations in existing approaches.

Keywords:
Dermatology, Skin Lesion, Fungal Infection, Diagnosis, Accuracy, Machine learning algorithms.

How to Cite:

[1] Kavyashree G J, Kavyashree Nagarajaiah, “A Comparative Analysis of Machine Learning Models and Data Sources towards Effective Skin Disease Prediction,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2026.13210

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.