Eczema predication based on AI Model
Year: 2025
Type: article
Abstract: In this paper we have proposed AI-based model for predicting eczema from medical skin image data set. Skin diseases are endemic health issues, usually leading to physical discomfort and mental depression, with extreme situations resulting in skin cancer. Identifying skin diseases manually is time- consuming and dependent on subjective decision-making, so automated systems are required. The most prevalent skin disease, eczema, is hard to identify because it has similar symptoms. We proposes a CNN-based AI system for the classification of eczema skin disease. The model consists of convolutional layers , feature extraction, pooling, and classification dense layers. Data augmentation is applied to improve performance. Accuracy, precision, recall, and F1-score are calculated. Classification accuracy is 98.2% and maintain reliable diagnosis with improved patient treatment efficiency. Key Words: CNN, eczema, AI , Skin disease
DOI: 10.55041/ijsrem42418
Authors: Dr S Brindha, Thamaraiselvi K, Gaviya A J, Nithika B, Preetha Raj, Srinithi R
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408452254