Inspiration
The misdiagnosis of breast cancer rate in the U.S. and around the world is high. There is a need of using machine to help the doctor interpret the cancerous tissue.
What it does
An evaluation of physical features of cancer and a revolutionary cancerous region and tumor type prediction algorithm.
How we built it
Deep learning and machine learning networks in python libraries.
Challenges we ran into
Writing the models in general is pretty challenging. We need to learn the libraries like tensorflow and eli5.
Accomplishments that we're proud of
Go ahead and check it out in our video, it is awesome!
What we learned
There is a great space for us to improve our model and networks.
What's next for Analysis of the Diagnosis of Breast Cancer Dataset
We have put our in the future plan section in the video: user interface, cancer stages, and more complex networks!
Log in or sign up for Devpost to join the conversation.