INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Abstract-Skin disease detection is a challenging task that requires expertise and experience. In this paper, we propose a machine learning-based approach for skin disease detection that can accurately diagnose different types of skin diseases. The proposed skin disease detection system uses machine learning algorithms to accurately detect and classify various skin diseases. The system takes input in the form of skin images and uses convolutional neural networks for feature extraction and classification. The accuracy of the system is evaluated using various metrics, and the results show that the proposed system outperforms existing methods in terms of accuracy and computational efficiency. We evaluate our approach on a large dataset of skin images and achieve a high accuracy rate of 95.6%. Our results show that machine learning can be an effective tool for skin disease detection and can help improve diagnostic accuracy. In this paper, we propose a skin disease detection system that uses machine learning algorithms. Our system aims to accurately and efficiently identify various skin diseases from images of skin lesions. We evaluated the performance of our proposed system using various machine learning algorithms and achieved an accuracy of over 90% on the test dataset. Our results demonstrate the potential of machine learning algorithms in improving the accuracy and efficiency of skin disease diagnosis.
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Cite Article:
"Skin Disease Detection Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.573 - 576, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304105.pdf
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Publication Details:
Published Paper ID: IJSDR2304105
Registration ID:204822
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 573 - 576
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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