Predicting Adherence to Home-Based Cardiac Rehabilitation with Data-Driven Methods
| Title: | Predicting Adherence to Home-Based Cardiac Rehabilitation with Data-Driven Methods |
|---|---|
| Authors: | Filos, Dimitris; Claes, Jomme; Cornelissen, Veronique; Kouidi, Evangelia; Chouvarda, Ioanna |
| Source: | ISSN:2076-3417 ; Applied Sciences-Basel, vol. 13 (10), Art.No. ARTN 6120. |
| Publisher Information: | Multidisciplinary Digital Publishing Institute (MDPI) |
| Publication Year: | 2023 |
| Subject Terms: | Science & Technology; Physical Sciences; Technology; Chemistry; Multidisciplinary; Engineering; Materials Science; Physics; Applied; adherence; cardiac rehabilitation; machine learning; prediction; exercise; home-based; familiarization phase; telemonitoring; CORONARY-ARTERY-DISEASE; EXERCISE PROGRAMS; EUROPEAN-SOCIETY; LIFE-STYLE; RISK; INTERVENTION; EFFICACY; IMPACT; HEART |
| Description: | status: Published |
| Document Type: | article in journal/newspaper |
| File Description: | application/pdf |
| Language: | English |
| Relation: | https://lirias.kuleuven.be/handle/20.500.12942/721571; https://doi.org/10.3390/app13106120 |
| DOI: | 10.3390/app13106120 |
| Availability: | https://lirias.kuleuven.be/handle/20.500.12942/721571; https://hdl.handle.net/20.500.12942/721571; https://lirias.kuleuven.be/retrieve/8ae7a4ac-332f-4caf-bf43-3478316fd469; https://doi.org/10.3390/app13106120 |
| Rights: | info:eu-repo/semantics/openAccess ; public ; All rights reserved |
| Accession Number: | edsbas.E390BA9B |
| Database: | BASE |