A Deep Learning-Based Framework for Early Detection of Systemic Diseases Using Nail Image Features

Pinnamraju Veeresh Kumar; kaki Priyanka; perla Raviteja; Shaik Janibasha; Talluri Satyaprakash

doi:10.36948/ijfmr.2026.v08i02.72549

A Deep Learning-Based Framework for Early Detection of Systemic Diseases Using Nail Image Features

Author(s)	Mr. Pinnamraju Veeresh Kumar, kaki Priyanka, perla Raviteja, Shaik Janibasha, Talluri Satyaprakash
Country	India
Abstract	Nail morphology serves as a non-invasive biological window into underlying systemic health conditions. Abnormalities in nail texture, pigmentation, and surface structure have long been associated with disorders including anemia, psoriasis, onychomycosis, thyroid dysfunction, and cardiovascular disease. Despite this clinical relevance, automated screening tools for nail-based disease identification remain limited in availability and diagnostic scope. This work introduces a deep learning framework designed to classify nail images into 18 distinct categories encompassing 17 pathological conditions and one healthy reference class. The methodology adopts the VGG16 convolutional architecture with ImageNet-initialized transfer weights, which are fine-tuned on a curated dermatological nail image collection. Image enhancement and augmentation strategies are incorporated to strengthen model robustness. The trained classifier demonstrates an overall recognition rate of 91.4% on held-out test data, establishing its viability as a supplementary screening instrument. System deployment is achieved through a lightweight Flask web interface that enables users to submit nail photographs and obtain instant diagnostic estimates accompanied by confidence metrics. The proposed solution holds significant promise for integration into telemedicine workflows, remote health monitoring systems, and community-level screening initiatives.
Keywords	Systemic Disease Screening, Nail Image Analysis, VGG16, Convolutional Neural Network, Transfer Learning, Medical Image Classification, Flask Deployment, Telemedicine, Deep Learning Healthcare
Field	Computer > Data / Information
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-27
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.72549

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A Deep Learning-Based Framework for Early Detection of Systemic Diseases Using Nail Image Features

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