Skin Disease Detection Using CNN

Skin Disease Detection Using CNN

Prof. Rekha Sahare Department of Computer Science and Engineering, Government College of Engineering Chandrapur, Maharashtra, India.

Email: - rekhasahare@gcoec.ac.in

Irfan Ahmad Kumar, Imran Ahmad Bhat, Anil Rupnar.

Department of Computer Science and Engineering, Government College of Engineering Chandrapur, Maharashtra, India.

1. Abstract

This study explores using advanced computer technology, specifically Convolutional Neural Networks (CNNs), for diagnosing diseases. By training the computer model with a variety of medical images, it learns to recognize patterns associated with different illnesses. The research investigates how well the model can accurately and quickly identify various medical conditions. Factors like the quality of the dataset, the design of the model, and fine-tuning its settings are considered. The results suggest that this method could enhance disease diagnosis speed and accuracy, contributing to discussions on AI's role in healthcare. Skin diseases are common across all age groups and a major source of infection in sub-Saharan Africa. Traditional diagnosis methods involve multiple tests, making the process laborious and time-consuming, requiring in-depth domain knowledge.