To develop a deep learning model based on Convolutional Neural Networks (CNN) for the early detection of skin cancer in educational settings.
To enhance the understanding of artificial intelligence and machine learning concepts among students through hands-on experience with real-world healthcare applications.
To evaluate the performance of the proposed CNN model in accurately classifying skin cancer images and compare it with traditional methods used in the medical field.
To provide a practical learning opportunity for students to apply their knowledge of AI and ML algorithms in a healthcare context.
Collect and preprocess a dataset of skin cancer images for training and testing the CNN model.
Implement and train the CNN model using popular deep learning frameworks such as TensorFlow or PyTorch.
Evaluate the performance of the model using metrics such as accuracy, precision, recall, and F1 score.
Compare the results of the CNN model with existing methods for skin cancer detection.
Write a research report documenting the project methodology, results, and findings for academic publication.
