Classification and detection of skin diseases based on CNN-powered image segmentation

Skin diseases have become more prevalent in recent years, posing a significant burden on healthcare systems globally. These conditions can range from noncancerous problems like acne, eczema, and vitiligo to more severe diseases such as melanoma, basal and squamous cell carcinoma. Skin ailments not only have an impact on physical health but can also affect the patient's psychological well-being, especially when the face is disfigured or damaged. Early detection and diagnosis of dermatological conditions can significantly improve survival rates as their severity can worsen over time. This article covers various methods used to identify and diagnose skin diseases, including natural diagnostic techniques and image pre-processing mechanisms and classification algorithms used globally. By understanding these techniques, healthcare professionals can detect skin diseases accurately, leading to better patient outcomes. Advancements in technology and research in this field continue to progress, providing hope to those who suffer from skin diseases.