Advanced Neural Network Approaches for Identifying and Diagnosis of Skin Cancer

Authors: Shital Bedse, Kiran Shinde, Piyush Wagh, Rohit Pawar, Zaid Shah

Country: India

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Abstract: Skin cancer is a type of cancer that grows in the skin tissue, which can cause damage to the surrounding tissue, disability, and even death. The accuracy of diagnosis and the early proper treatment can minimize and control the harmful effects of skin cancer. Due to the similar shape of the lesion between skin cancer and benign tumor lesions, physicians consuming much more time in diagnosing these lesions. The system was developed in this study could identify skin cancer and benign tumor lesions automatically using the Convolutional Neural Network (CNN). This project introduces a novel application of advanced neural network techniques to facilitate the identification and diagnosis of skin cancer. The core of this approach lies in its utilization of deep learning, particularly through convolutional neural networks (CNNs), to effectively analyze skin images uploaded for examination. The system extends its impact beyond diagnosis by providing personalized recommendations for skin cancer prevention.

Keywords: Convolutional Neural Network, Deep Learning, Transfer Learning, Skin Cancer

Paper Id: 230439

Published On: 2024-01-16

Published In: Volume 12, Issue 1, January-February 2024

Cite This: Advanced Neural Network Approaches for Identifying and Diagnosis of Skin Cancer - Shital Bedse, Kiran Shinde, Piyush Wagh, Rohit Pawar, Zaid Shah - IJIRMPS Volume 12, Issue 1, January-February 2024.

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