Nositelná elektronika (wearables), telemedicína a umělá inteligence u arytmií a srdečního selhání: Zápis z kulatého stolu Evropské kardiologické společnosti na téma kardiovaskulární onemocnění. Překlad dokumentu připravený Českou kardiologickou společností

Title in English Wearables, telemedicine, and artificial intelligence in arrhythmias and heart failure: Proceedings of the European Society of Cardiology Cardiovascular Round Table. Translation of the document prepared by the Czech Society of Cardiology
Authors

TABORSKY Milos KAUTZNER Josef FEDORCO Marian CURILA Karol WUNSCHOVA Hanka PYSZKO Jan NOVÁK Miroslav KOZÁK Milan VALEK Martin POLASEK Rostislav KEPRT Patrik KUBICKOVA Milena PLASEK Jiri GLOGER Vit BULAVA Alan VANCURA Vlastimil SKALA Tomas PARIZEK Petr DANEK Josef

Year of publication 2022
Type Article in Periodical
Magazine / Source cor et Vasa
MU Faculty or unit

Faculty of Medicine

Citation
Web https://e-coretvasa.cz/artkey/cor-202206-0012_wearables-telemedicine-and-artificial-intelligence-in-arrhythmias-and-heart-failure-proceedings-of-the-euro.php
Doi http://dx.doi.org/10.33678/cor.2022.123
Keywords Artificial intelligence; Digital healthcare solutions; Early detection; M-health; Monitoring; Wearable devices
Description Digital technology is now an integral part of medicine. Tools for detecting, screening, diagnosis, and monitoring health-related parameters have improved patient care and enabled individuals to identify issues leading to better management of their own health. Wearable technologies have integrated sensors and can measure physical activity, heart rate and rhythm, and glucose and electrolytes. For individuals at risk, wearables or other devices may be useful for early detection of atrial fibrillation or sub-clinical states of cardiovascular disease, disease management of cardiovascular diseases such as hypertension and heart failure, and lifestyle modification. Health data are available from a multitude of sources, namely clinical, laboratory and imaging data, genetic profiles, wearables, implantable devices, patient-generated measurements, and social and environmental data. Artificial intelligence is needed to efficiently extract value from this constantly increasing volume and variety of data and to help in its interpretation. Indeed, it is not the acquisition of digital information, but rather the smart handling and analysis that is challenging. There are multiple stakeholder groups involved in the development and effective implementation of digital tools. While the needs of these groups may vary, they also have many commonalities, including the following: a desire for data privacy and security; the need for understandable, trustworthy, and transparent systems; standardized processes for regulatory and reimbursement assessments; and better ways of rapidly assessing value.

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