Built a CNN based model which can accurately detect melanoma. Melanoma is a type of cancer that can be deadly if not detected early. It accounts for 75% of skin cancer deaths. A solution which can evaluate images and alert the dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.

• General Info
• Technologies Used
• Conclusions

• A solution which can evaluate images and alert the dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.
• The dataset consists of 2357 images of malignant and benign oncological diseases, which were formed from the International Skin Imaging Collaboration (ISIC)

• Python
• Keras
• Tensorflow
• Augmentor
• Numpy
• Pandas

• Accuracy on initial data - Training: 0.9035, Validation: 0.2609
• Accuracy on optimised and agumented data - Training: 0.4799 , Validation: 0.3043
• Accuracy on class rebalanced data - Training: 0.9566 , Validation: 0.8151

Created by @prasoonmhwr - feel free to contact me!