• K.L.GANAPATHIREDDY
• Dr Akula Siva Prasad

In this Modern era due to Globalization, increase in the environment pollution , many people across the world are exposed to Skin related diseases which might be a global health issue leading to severe complications leads to skin cancer if not diagnosed and treated promptly. Skin cancer detection is difficult because of differences in lesion size, shape, and severity. Although many traditional methods followed by the dermatologists diagnosing skin conditions relies on manual examination process that can be a time taken and susceptible to human error. Moreover,in rural and remote areas access to skilled dermatologists is often limited.due to advancement in the technologies like Machine Learning Models there might be some inaccurate prediction based on the skin images. To tackle these problems in this paper we propose a CNN based deep learning Technique which automates the detection of Skin related diseases by analyzing dermoscopic Images.here we designed the system to classify and early detection of the skin diseases like melanoma, eczema, psoriasis, and others catastrophic skin cancers, offering valuable support for effective treatment planning.

Skin Disease classification, Convolutional Neural Networks (CNN), Deep Learning, Machine Learning,Dermoscopic Images, Melanoma , Eczema Classification, Psoriasis Diagnosis, Image Processing, Automated Diagnosis.

"An Effective Skin Disease Classification and Prediction Using Deep Learning Model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.171-176, May-2025, Available :http://www.jetir.org/papers/JETIRGV06024.pdf

"An Effective Skin Disease Classification and Prediction Using Deep Learning Model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp171-176, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06024.pdf