A predictive Alzheimers model exploring how variables like age, BMI, and functional assessments influence neurological risk over time.
NeuroCurve builds live risk curves which predict risk of Alzheimer's by simulating how improvements in human activities can influence risk. It combines a Neural Network with visualization tools to help interpret risk trajectories for individual patients.
- Age-Risk Simulation: Modify patient age, diet quality, sleep quality, exercice, and/or BMI scores to predict risk.
- Easy-to-Use: Plug in your trained model and patient features to visualize risk over time.
- Visualization: Clear plots drawing predicted risk progression.
This project was created by:
Adam Timney
Andrew Alexander Sam
Brady Spak
Conrad Oldoerp
Spencer Oldoerp
Special thanks to Aditya Patil.
https://www.kaggle.com/datasets/rabieelkharoua/alzheimers-disease-dataset
https://docs.google.com/presentation/d/160ooftiwjojsqxU1C9HAUH0-lmQBDBMGRZGvk5JmuCc/edit?usp=sharing
git clone https://github.com/Spakshots/NeuroCurve.git
cd NeuroCurve
pip install -r requirements.txt