Eczema predication based on AI Model

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

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-14
DOI
https://doi.org/10.55041/ijsrem42418
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Eczema predication based on AI Model

K. Thamaraiselvi, P.V. Tharunn Raj, D. Brindha, A J Gaviya et al.
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Cutaneous Melanoma Detection and Management
article

Eczema predication based on AI Model

K. Thamaraiselvi, P.V. Tharunn Raj, D. Brindha, A J Gaviya, B Nithika, R Srinithi
article en

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

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Openalex Percentile: Top 93%
Cutaneous Melanoma Detection and Management
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