The field of dermatological diagnosis has made significant strides recently with the application of AI and machine learning approaches. The aim of the study is to investigate the potential of AI and machine learning technologies in diagnosing and predicting skin diseases. Research has utilized techniques including convolutional neural networks, deep learning, and ensemble data mining to identify a variety of skin disorders with high accuracy rates, frequently between 88 and 100 Percentage. Even with these advancements, there are still issues to be resolved, such as the scarcity of datasets and uncertainties regarding practicality. Still, there is great potential for revolutionizing dermatological diagnoses with new methods that combine deep learning and computer vision. In order to really use these technologies in clinical settings, more testing and improvement are required.
Author
(s) Details
Tharigopula
Madhan Mohan
Department of Computer Science, Christ (Deemed to be a
University), Bengaluru, India.
Smera C
Department of Computer Science, Christ (Deemed to be a
University), Bengaluru, India.
Sandeep
J
Department of Computer Science, Christ (Deemed to be a
University), Bengaluru, India.
Sreeja
CS
Department of Computer Science, Christ (Deemed to be a
University), Bengaluru, India.
Karthik
Raja
Department of Computer Science, Christ (Deemed to be a University),
Bengaluru, India.
John
Gilbert
Department of Computer Science, Christ (Deemed to be a
University), Bengaluru, India.
Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-49238-47-3/CH16
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