Authors - Shriya Vadavalli, Geethika Bodagala, T Sridevi Abstract - This paper conducts a systematic literature review about the current status of the art in the detection and diagnosis of autoimmune skin diseases. This paper identifies recent studies and advancements in terms of key technologies, methodologies, and approaches used in this domain specifically with regard to imaging and deep learning techniques. Therefore, the work underlines scopes for further studies in terms of improving diagnostics accuracy and increasing robustness and accessibility for diagnostic solutions. This piece of work also puts a hole in the existing literature, and research gaps on machine learning algorithms and image processing have highlighted the enhancement of the precision as well as effectiveness of such detection systems with respect to skin diseases. This review is in a position to provide grounds for future research directions and innovations in skin disease diagnostics.
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