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Predictive Modelling and Its Visualization for Telehealth Data - Concept and Implementation of an Interactive Viewer
Michael Sams1, Alphons Eggerth1, Dieter Hayn1
1AIT Austrian Institute of Technology, Graz, Austria.
Studies in Health Technology and Informatics
|May 24, 2019
Summary
A new toolset aids data scientists in developing predictive models for telehealth. This viewer enhances understanding of model development and predictions, crucial for healthcare adoption.
Area of Science:
- Health Informatics
- Machine Learning in Healthcare
Background:
- Predictive modeling is vital in healthcare for system development and acceptance.
- Understanding models and predictions is essential for clinical integration.
Purpose of the Study:
- Develop a conceptual toolset for data scientists.
- Implement a system supporting predictive model development in telehealth.
Main Methods:
- User requirements gathered through surveys.
- Concept development based on 'HerzMobil Tirol' telehealth data model.
- Implementation utilizing MATLAB.
Main Results:
- Identified a comprehensive list of user requirements.
- Successfully implemented a viewer tool based on identified requirements.
Conclusions:
- The developed viewer provides deeper insights into predictive model development.
- Enhanced understanding facilitates better acceptance of telehealth predictive systems.
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