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A Comprehensive Review of Machine Learning Techniques for Automatic Skin Disease Detection

Authors :

Mahdie Naseri¹ Azita Shirazipour² Seyed Javad Mirabedini³

1- Department of Computer, CT.C., Islamic Azad University, Tehran, Iran 2- Department of Computer, CT.C., Islamic Azad University, Tehran, Iran 3- Department of Computer, CT.C., Islamic Azad University, Tehran, Iran

Keywords :

Machine Learning،Deep Learning،Skin Disease Detection،Computer Vision،Medical Imaging

Abstract :

This study offers a thorough analysis of machine learning (ML) methods for automatically identifying skin conditions, emphasizing developments in both technology and algorithms. Medical imaging and the increasing incidence of dermatological disorders have made ML crucial for precise and effective diagnosis. We examine and highlight the advantages and disadvantages of deep learning architectures, conventional machine learning algorithms, and new hybrid approaches. Evaluation metrics, preprocessing methods, and datasets utilized in the field are all covered in the review. Important issues like data imbalance, computational complexity, and model generalizability are addressed, along with potential future paths to increase algorithmic effectiveness and practicality. For researchers looking to develop automated dermatological diagnostics, this study is a valuable technical resource.

Papers List

List of archived papers

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