Alzheimer's Drug Repurposing Analysis

Upload your CSV data to perform comprehensive causal AI analysis including directional feature importance and uplift tree analysis

If left empty, drug name will be inferred from filename

Data Format Requirements

Required columns: Drug (binary), AD (binary outcome), demographic features (continuous), clinical features (binary/continuous)

Analysis includes:

  • CFR-based treatment effect analysis
  • Directional feature importance analysis
  • Uplift tree visualizations
  • Individual Treatment Effect (ITE) analysis

Example format:

Drug,AD,Age,Gender,Diabetes,Hypertension,MMSE_Score
1,0,65,1,0,1,28
0,1,72,0,1,0,24
...

Note: The analysis will generate comprehensive visualizations including directional feature effects and uplift tree analysis.

Upload Your Data

or drag and drop

CSV files only, up to 10MB

Select Analysis Models

Choose one or more models for your analysis. Each model uses different approaches to measure distribution differences.

MMD Linear

Maximum Mean Discrepancy with linear kernel

MMD RBF

Maximum Mean Discrepancy with RBF kernel

Wasserstein

Wasserstein distance metric

Training Configuration

Configure the number of training epochs for the models. More epochs may improve accuracy but take longer to train.

10
150
Recommended: 10-20 epochs for faster analysis, 30-50 for higher accuracy
Create Next App