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Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation.

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第一作者: Hélène,De Cannière
第一单位: Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium.;Future Health Department, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium.
作者单位: Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium.;Future Health Department, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium. [1] imec the Netherlands/Holst Centre, 5656AE Eindhoven, The Netherlands. [2] Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium.;Future Health Department, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium.;imec the Netherlands/Holst Centre, 5656AE Eindhoven, The Netherlands. [3] KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, 3001 Leuven, Belgium.;TU Delft, Department of Microelectronics, Circuits and Systems (CAS), 2600AA Delft, The Netherlands. [4] KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, 3001 Leuven, Belgium.;imec vzw Belgium, 3001 Leuven, Belgium. [5] KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, 3001 Leuven, Belgium. [6] Mobile Health Unit, Faculty of Medicine and Life Sciences, Hasselt University, 3500 Hasselt, Belgium.;Future Health Department, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium.;Department of Cardiology, Ziekenhuis Oost-Limburg, 3600 Genk, Belgium. [7]
DOI 10.3390/s20123601
PMID 32604829
发布时间 2023-11-11
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Sensors (Basel, Switzerland)

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