A practical research companion
Machine Learning
with MAIT
A practical guide to classification, survival analysis, regression, and model interpretation
From research data to interpretable models
MAIT—the Medical Artificial Intelligence Toolbox—brings data preparation, model evaluation, and explanation into one Python workflow for tabular research data. This book walks through binary classification, survival analysis, and regression, with worked examples and guidance for interpreting the outputs.
For researchers working with clinical, biological, or other tabular datasets. Start with a tutorial, then use the manual to explore the methods and configuration options.
Get MAIT on GitHub · Run the Python package demo · Function reference
About this project
MAIT was developed by Ramtin Zargari Marandi, PhD during his postdoctoral work at PERSIMUNE–CHIP, Rigshospitalet, Copenhagen University Hospital, with contributions from Anne Svane Frahm, PhD, Jens D. Lundgren, MD, DMSc, Maja Milojevic, PhD, and Daniel Dawson Murray, PhD.
If MAIT contributes to your research, please cite the MAIT methods paper. Full citation details are available in the repository.