@inproceedings{8659709391dc4e9c9c0e521ab3e3d260,
title = "Integration of Python Modules in a MATLAB-Based Predictive Analytics Toolset for Healthcare",
abstract = "Background: Python and MATLAB both are common tools used for predictive modelling applications, not only in healthcare. In our predictive modelling group, both tools are widely used. None of the two tools is optimal for all tasks along the value chain of predictive modelling in healthcare. Objectives: The aim of this study was to explore different ways to extend our MATLAB-based toolset with Python functions. Methods: Pre-existing interfaces between MATLAB and Python have been evaluated and more comprehensive interfaces have been designed to exchange even complex data formats such as MATLAB tables. Results: The interfaces have successfully been implemented and they were validated in a Natural Language Processing scenario based on free-text notes from a telehealth services for heart failure patients. Conclusion: Integration of Python modules in our MATLAB toolset is possible. Further improvements especially in terms of performance, are required if large datasets need to be exchanged. A big advantage of our concept is that tabular data can be exchanged between MATLAB and Python without loss and the Python functions are called dynamically via the interface.",
keywords = "Data exchange, Interfacing, Machine learning, MATLAB, Predictive Analytics, Python",
author = "Lukas Haider and Martin Baumgartner and Dieter Hayn and Guenter Schreier",
note = "Funding Information: This work was performed in the context of the d4HealthTirol project, which is funded by the Land Tirol. Publisher Copyright: {\textcopyright} 2022 The authors, AIT Austrian Institute of Technology and IOS Press.; 16th Annual Health Informatics Meets Digital Health Conference : dHealth 2022 ; Conference date: 24-05-2022 Through 25-05-2022",
year = "2022",
month = may,
day = "16",
doi = "10.3233/SHTI220369",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "197--204",
editor = "Bernhard Pfeifer and Martin Baumgartner",
booktitle = "dHealth 2022 - Proceedings of the 16th Health Informatics Meets Digital Health Conference",
}