Code for fusion of tabular data (from electronic health records) and radiographs (x-ray images) for classification of atypical and normal femur fractures.

Used in the paper

Schilcher, J., Nilsson, A., Andlid, O., & Eklund, A. (2024). Fusion of electronic health records and radiographic images for a multimodal deep learning prediction model of atypical femur fractures. Computers in Biology and Medicine, 168, 107704.

https://doi.org/10.1016/j.compbiomed.2023.107704

If you use the code, please cite the paper.

Prepare dataset (in this case, a csv file with all tabular data, and a directory with PNG images, to match the two types of data each PNG filename contains a patient number which corresponds to that row in the csv file)

Create and activate anaconda environment

Run train_several_models.py

Preparation code written by Anders Eklund

Original analysis code written by Alva Nilsson and Oliver Andlid, extended and modified by Anders Eklund