Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Tariq Osman Andersen"'
Autor:
Stina Matthiesen, Søren Zöga Diederichsen, Mikkel Klitzing Hartmann Hansen, Christina Villumsen, Mats Christian Højbjerg Lassen, Peter Karl Jacobsen, Niels Risum, Bo Gregers Winkel, Berit T Philbert, Jesper Hastrup Svendsen, Tariq Osman Andersen
Publikováno v:
JMIR Human Factors, Vol 8, Iss 4, p e26964 (2021)
BackgroundArtificial intelligence (AI), such as machine learning (ML), shows great promise for improving clinical decision-making in cardiac diseases by outperforming statistical-based models. However, few AI-based tools have been implemented in card
Externí odkaz:
https://doaj.org/article/6a60bfb505a74ec89622e1750345649c
Publikováno v:
Big Data & Society, Vol 7 (2020)
Personal health technologies such as apps and wearables that generate health and behavior data close to the individual patient are envisioned to enable personalized healthcare - and self-care. And yet, they are consumer devices. Proponents of these d
Externí odkaz:
https://doaj.org/article/8f0c7f6393324c4da7f1437eb9bea852
Autor:
Saeed Shakibfar, Oswin Krause, Casper Lund-Andersen, Filip Strycko, Jonas Moll, Tariq Osman Andersen, Helen Høgh Petersen, Jesper Hastrup Svendsen, Christian Igel
Publikováno v:
PLoS ONE, Vol 14, Iss 8, p e0219533 (2019)
BackgroundAntitachycardia pacing (ATP) is an effective treatment for ventricular tachycardia (VT). We evaluated the efficacy of different ATP programs based on a large remote monitoring data set from patients with implantable cardioverter-defibrillat
Externí odkaz:
https://doaj.org/article/ba87efa5fba544b491a6814b9ad4828a
Publikováno v:
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems.
Autor:
Maarten Z.H. Kolk, D.M. Frodi, Fleur V.Y. Tjong, Hanno L. Tan, Tariq Osman Andersen, Reinoud E. Knops, Joss Langford, Soeren Z. Diederichsen, Jesper Hastrup Svendsen
Publikováno v:
Cardiovascular Digital Health Journal, 2(6), S11-S20. Elsevier Inc.
Frodi, D M, Kolk, M Z H, Langford, J, Andersen, T O, Knops, R E, Tan, H L, Svendsen, J H, Tjong, F V Y & Diederichsen, S Z 2021, ' Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy ', Cardiovascular Digital Health Journal, vol. 2, no. 6, pp. S11-S20 . https://doi.org/10.1016/j.cvdhj.2021.10.002
Cardiovascular Digital Health Journal, Vol 2, Iss 6, Pp S11-S20 (2021)
Frodi, D M, Kolk, M Z H, Langford, J, Andersen, T O, Knops, R E, Tan, H L, Svendsen, J H, Tjong, F V Y & Diederichsen, S Z 2021, ' Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy ', Cardiovascular Digital Health Journal, vol. 2, no. 6, pp. S11-S20 . https://doi.org/10.1016/j.cvdhj.2021.10.002
Cardiovascular Digital Health Journal, Vol 2, Iss 6, Pp S11-S20 (2021)
BackgroundPatients with an implantable cardioverter-defibrillator (ICD) are at a high risk of malignant ventricular arrhythmias. The use of remote ICD monitoring, wearable devices, and patient-reported outcomes generate large volumes of potential val
Autor:
Diana My Frodi, Jesper Hastrup Svendsen, Katarzyna Wac, Vlad Manea, Søren Zöga Diederichsen, Tariq Osman Andersen
Publikováno v:
Journal of Personalized Medicine; Volume 12; Issue 6; Pages: 942
Frodi, D M, Manea, V, Diederichsen, S Z, Svendsen, J H, Wac, K & Andersen, T O 2022, ' Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator : An Exploratory Observational Study ', Journal of Personalized Medicine, vol. 12, no. 6, 942, pp. 1-34 . https://doi.org/10.3390/jpm12060942
Frodi, D M, Manea, V, Diederichsen, S Z, Svendsen, J H, Wac, K & Andersen, T O 2022, ' Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator : An Exploratory Observational Study ', Journal of Personalized Medicine, vol. 12, no. 6, 942, pp. 1-34 . https://doi.org/10.3390/jpm12060942
Ventricular arrhythmia (VA) is a leading cause of sudden death and health deterioration. Recent advances in predictive analytics and wearable technology for behavior assessment show promise but require further investigation. Yet, previous studies hav
Autor:
Søren Zöga Diederichsen, R.E. Knops, Tariq Osman Andersen, M.Z.H. Kolk, Jesper Hastrup Svendsen, D.M. Frodi, F.V.Y. Tjong, J. Langford, Hanno L. Tan
Publikováno v:
Kolk, M Z H, Frodi, D M, Andersen, T O, Langford, J, Diederichsen, S Z, Svendsen, J H, Tan, H L, Knops, R E & Tjong, F V Y 2022, ' Accelerometer-assessed physical behavior and the association with clinical outcomes in implantable cardioverter-defibrillator recipients : A systematic review ', Cardiovascular Digital Health Journal, vol. 3, no. 1, pp. 46-55 . https://doi.org/10.1016/j.cvdhj.2021.11.006
Background Current implantable cardioverter defibrillator (ICD) devices are equipped with a device-embedded accelerometer capable of capturing physical activity (PA). In contrast, wearable accelerometer-based methods enable the measurement of physica
Autor:
Tariq Osman Andersen
Publikováno v:
Interactions. 26:74-77
This forum is dedicated to personal health in all its many facets: decision making, goal setting, celebration, discovery, reflection, and coordination, among others. We look at innovations in interactive technologies and how they help address current
Autor:
D.M. Frodi, Tariq Osman Andersen, Hanno L. Tan, Søren Zöga Diederichsen, Mzh Kolk, Jesper Hastrup Svendsen, F V Y Tjong, J. Langford, Reinoud E. Knops
Publikováno v:
EP Europace. 23
Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Eurostars Introduction Patients at a high risk of sudden cardiac death (SCD) benefit from an implantable cardioverter defibrillator (ICD). Howev
Autor:
Stina Matthiesen, Søren Zöga Diederichsen, Mikkel Klitzing Hartmann Hansen, Christina Villumsen, Mats Christian Højbjerg Lassen, Peter Karl Jacobsen, Niels Risum, Bo Gregers Winkel, Berit T Philbert, Jesper Hastrup Svendsen, Tariq Osman Andersen
BACKGROUND Artificial intelligence (AI), such as machine learning (ML), shows great promise for improving clinical decision-making in cardiac diseases by outperforming statistical-based models. However, few AI-based tools have been implemented in car
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df514d24a4b06a5f0cd224aacca6f975
https://doi.org/10.2196/preprints.26964
https://doi.org/10.2196/preprints.26964