This repo contains the code for running machine learning (ML)-based surrogate models in the paper " Surrogate models based onmachine learning methods for parameter estimation of leftventricular myocardium "

we use three ML-based surrogate models, namely K-nearest neighbour(KNN) , XGBoost and multi-layer perceptron . The three chosen ML models can be considered to be a supervised learning regression problem. After training process, we further apply the three ML-based surrogate models for parameter estimation.

The code requires Matlab2016, Python (3.6+) and the following dependencies: scikit-learn, pandas, numpy, Scipy, xgboost ,joblib.

To setup, either run, you can download this repo and better prepare a pip environment:

cd .
pip install --upgrade pip
pip install -r requirements.txt