| Creators: | Pryss, Rüdiger and Schickler, Marc and Schobel, Johannes and Schlee, Winfried and Spiliopoulou, Myra and Probst, Thomas and Beierle, Felix |
|---|---|
| Title: | Using Machine Learning on mHealth-based Data Sources (Tutorial) |
| Item Type: | Conference or Workshop Item |
| Event Title: | (Proceedings of the) 20th International Conference on Artificial Intelligence in Medicine (AIME) |
| Event Location: | Halifax, NS, Canada |
| Event Dates: | June, 14-17, 2022 |
| Projects: | DigiHealth |
| Page Range: | pp. 443-445 |
| Date: | 2022 |
| Divisions: | Gesundheitsmanagement |
| Abstract (ENG): | The application of machine learning algorithms has become important for the medical domain. However, the concrete application of these type of algorithms strongly depends on how a corresponding data source was created. Most importantly, domain knowledge must be linked with data science knowledge. Data collected using smartphones or smart mobile devices (e.g., smart watches) is commonly referred to as mHealth data. The possibilities and strategies for collecting data in this area now appear to be as diverse as the machine learning algorithms that have emerged. This tutorial will therefore discuss how mHealth data is structured and which aspects need to be taken into account when evaluating it with machine learning algorithms, using concrete examples |
| Forthcoming: | No |
| Language: | English |
| Uncontrolled Keywords: | mHealth ; Machine learning ; Data collection strategies |
| Citation: | Pryss, Rüdiger and Schickler, Marc and Schobel, Johannes and Schlee, Winfried and Spiliopoulou, Myra and Probst, Thomas and Beierle, Felix (2022) Using Machine Learning on mHealth-based Data Sources (Tutorial). In: (Proceedings of the) 20th International Conference on Artificial Intelligence in Medicine (AIME), June, 14-17, 2022, Halifax, NS, Canada, pp. 443-445. (Lecture Notes in Computer Science; 13263). ISBN 9783031093425 |
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