Using biomarker data from various cancer antigens, we developed a neural network capable of detecting pancreatic cancer with an accuracy of 67%.
This project won 🏆Best Data/Infosec hack 🏆 at FraserHacks
Read the Devpost here
Check out the slides here
Check out the code here
🔍What it does
Our machine learning model takes in biomarker data for cancer antigens as inputs, and predicts your chances of having pancreatic cancer. This can be used to either validate a doctor’s opinion quickly and easily.
🔨How I built it
We built our model in the Python language, with the Keras library with TensorFlow as a backend. This was done in Google Colab and Sublime Text for building and iteratively optimizing our model.