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Skin Disease Detection using Machine Learning

  • Unique Paper ID: 162927
  • Volume: 10
  • Issue: 11
  • PageNo: 453-456
  • Abstract:
  • The project aims to develop a skin disease detection system using machine learning techniques. Leveraging image processing and classification algorithms, the system will analyze dermatological images to accurately identify various skin conditions. By employing convolutional neural networks (CNNs) trained on extensive datasets of labeled images, the system will learn to recognize patterns and features indicative of different diseases such as eczema, psoriasis, melanoma, and others. The proposed system seeks to provide a non-invasive, cost-effective, and efficient solution for early diagnosis and treatment recommendation, aiding healthcare professionals in timely intervention. Through the integration of machine learning algorithms with a user-friendly interface, the system will enable easy access for both medical practitioners and patients, potentially reducing the burden on dermatologists and improving healthcare outcomes. This project holds promise in revolutionizing dermatological diagnostics, contributing to better patient care and management of skin diseases.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 11
  • PageNo: 453-456

Skin Disease Detection using Machine Learning

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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