Skin Diseases Classification with Deep Learning Techniques: A Review

One major health problem is the frequency of skin disorders. For treatment to be effective, a precise diagnosis is essential. Traditional diagnostic techniques, which frequently rely on dermoscopy and visual inspection, can be laborious and subjective. One possible method for automated skin disease diagnostics is a subset of artificial intelligence. This review explores the use of deep learning methods in this sector by looking at the many kinds of skin conditions. datasets using augmentation and preprocessing methods performance benchmarks and criteria for evaluating model designs We also go into the drawbacks and difficulties, such as interpretability of data quality models and ethical issues. By utilizing deep learning, we can increase the precision and effectiveness of diagnosing skin diseases, which will enhance patient outcomes.