Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The state of human health is often subtly yet profoundly reflected in the condition of the fingernails. As a non- invasive biometric canvas, the nail unit can display visual cues related to dozens of systemic ailments, ranging from common fungal infections (onychomycosis) to critical conditions like subungual melanoma and signs of organ dysfunction. However, current diagnostic practices face significant hurdles: namely, the reliance on subjective visual expertise, the limited resolution of the unaided human eye to detect subtle chromatic shifts, and the pervasive issue of global expert scarcity. This comprehensive literature review meticulously synthesizes contemporary research, focusing on the transformative application of Deep Learning (DL) methodologies to create a scalable, objective, and accessible diagnostic framework. We structure this review around three critical research areas: robust classification for initial diagnosis, advanced segmentation for quantifiable assessment, and the pressing challenges of system integration for real-world utility.
Keywords:
Deep Learning, Nail Disease Classification, Medical Image Analysis, Convolutional Neural Networks (CNNs), Transfer Learning (TL), Hybrid Capsule Networks, Gradient-weighted Class Activation Mapping (Grad-CAM), Mobile Diagnostics, Onychomycosis Detection, Subungual Melanoma Screening, Data Augmentation, Medical Image Robustness, Automated Diagnostic Systems, Clinical Decision Support.
Cite Article:
"Health Analysis and Recommendation System using Fingernail Images", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.a232-a239, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512031.pdf
Downloads:
000180
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator