Machine learning applied to wearable fitness tracker data and the risk of hospitalizations and cardiovascular events
Background: Wearable fitness trackers generate extensive physiological and activity data, offering potential to monitor health and predict outcomes. Machine learning (ML) techniques applied to these data may enable early identification of adverse health conditions, such as hospitalizations and devel...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | American Journal of Preventive Cardiology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666667725000819 |
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