Artificial Intelligence for Early Detection of Skin Cancer Using Deep Learning, Machine Learning and CNN

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Abstract Skin cancer is among the most common and life-threatening cancers worldwide. Early detection is the key to improving survival rates and reducing treatment costs. Traditional diagnostic approaches in dermatology rely on visual inspection and dermoscopy, which can be subjective and prone to errors. With the advent of Artificial Intelligence (AI) and deep learning, automated systems have shown remarkable accuracy in classifying skin lesions. This paper investigates the role of AI in enhancing diagnostic precision for early detection of skin cancer. A deep learning-based framework, particularly Convolutional Neural Networks (CNNs), is utilized to analyze dermoscopic images from datasets such as ISIC. The proposed system improves diagnostic performance by reducing misclassification and assisting dermatologists in decision-making. Results highlight the transformative potential of AI in dermatology, aiming to reduce mortality and improve patient survival through timely intervention

References

References :

 

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Keywords

Artificial Intelligence, Skin Cancer, Deep Learning, Dermatology, Diagnostic Precision.