Code supporting the paper: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations

doi: 10.4121/21257199.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21257199
Datacite citation style:
Egberts, Ginger; Vermolen, Fred; Zuijlen, Paul van (2023): Code supporting the paper: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/21257199.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software

This online resource shows three archived folders: Matlab, Python, and App that contain relevant code and data for the article: High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations. 


Within the Matlab folder, one finds the codes used for the generation of the large dataset. Here, the file Main.m is the main file and from there, one can run the Monte Carlo simulation.


Within the Python folder, one finds the codes used for training the neural networks and creating the online application. The file Data.mat contains the data generated by the Matlab Monte Carlo simulation. The files run_bound.py, run_rsa.py, and run_tse.py train the neural networks, of which the best scoring ones are saved in the folder Training. The DashApp folder contains the code for the creation of the Application.


Within the App folder, one finds the executable nn_R2_app.exe that one can run, once the archived folder is unzipped. When running the app, it opens in a browser. This was checked in Windows.

history
  • 2023-01-30 first online, published, posted
publisher
4TU.ResearchData
format
*.zip; *.m; *.mat; *.py; *.txt; *.png; *.exe;
funding
  • Dutch Burn Foundation, project 17.105.
organizations
TU Delft, Delft Institute of Applied Mathematics;

University of Hasselt, Department of Mathematics and Statistics;

Burn Centre and Department of Plastic, Reconstructive and Hand Surgery, Red Cross Hospital, Beverwijk, Netherlands;

Department of Plastic, Reconstructive and Hand Surgery, Amsterdam UMC;

Pediatric Surgical Centre, Emma Children's Hospital, Amsterdam UMC

DATA

files