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Survey Paper | Computer Science | Volume 15 Issue 6, June 2026 | Pages: 596 - 602 | India
A Survey and Analysis of Intelligent Detection for Nail Disease Diagnosis Using Artificial Intelligence
Abstract: Nail diseases present common dermatological pathologies that include both nail plate and the tissues around them, and they often represent clues of fungal infections and inflammatory diseases or underlying systemic pathologies. The incidence of nail disorders in the world has increased significantly, which explains the high significance of early and precise diagnosis of these complications and securing of proper treatment measures. Some diagnostic methods that are regularly used include dermoscopy, laboratory analysis and clinical examination. To make the process of automatic detection and categorization of nail diseases out of medical imagery possible, Machine Learning (ML) methods have been included to permit feature extraction, selection and classification. However, traditional ML algorithms rely heavily on hand-designed features, require a lot of preprocessing, and they are often prone to failure when faced with a complex and high-dimensional image dataset. To overcome these constraints, a more effective and advanced method has occurred, and this is known as Deep Learning (DL). Unlike the classical methodologies and classical ML algorithms, DL models automatically train hierarchical and discriminative feature directly on raw nail images hence providing better accuracy, strength, and scalability. The current research provides a systematic review and a survey of currently existing methods of detecting nail diseases based on the idea of DL, analyzing their structure, strengths, weaknesses and comparing their performances.
Keywords: Nail disease detection, Medical image classification, Machine Learning, Deep Learning
How to Cite?: V J Rajakumar, A Somasundaram, "A Survey and Analysis of Intelligent Detection for Nail Disease Diagnosis Using Artificial Intelligence", Volume 15 Issue 6, June 2026, International Journal of Science and Research (IJSR), Pages: 596-602, https://www.ijsr.net/getabstract.php?paperid=SR26609181129, DOI: https://dx.dx.doi.org/10.21275/SR26609181129