Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Per Niklas Waaler"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statisti
Externí odkaz:
https://doaj.org/article/07dd0ba9af47441283fc8e0ef4177906
Autor:
Per Niklas Waaler, Hasse Melbye, Henrik Schirmer, Markus Kreutzer Johnsen, Tom Donnem, Johan Ravn, Stian Andersen, Anne Herefoss Davidsen, Juan Carlos Aviles Solis, Michael Stylidis, Lars Ailo Bongo
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 10 (2024)
ObjectiveThis study aims to assess the ability of state-of-the-art machine learning algorithms to detect valvular heart disease (VHD) from digital heart sound recordings in a general population that includes asymptomatic cases and intermediate stages
Externí odkaz:
https://doaj.org/article/7011cc8c8a814877a26102362a5470e7
Background. If patients could utilise scientific research about modifiable risk factors there is a potential to prevent disease and promote health. Mobile applications can automatically adjust what and how information is presented based on a user's p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a812d595fc2c0846e21ae54ba737e357
https://doi.org/10.1101/2023.05.25.23290511
https://doi.org/10.1101/2023.05.25.23290511
Autor:
Per Niklas Waaler, Hasse Melbye, Henrik Schirmer, Markus Kreutzer Johnsen, Tom Dønnem, Johan Ravn, Stian Andersen, Anne Herefoss Davidsen, Juan Carlos Aviles-Solis, Michael Stylidis, Lars Ailo Bongo
BackgroundAlthough neural networks have shown promise in classifying pathological heart sounds (HS), algorithms have so far either been trained or tested on selected cohorts which can result in selection bias. Herein, the main objective is to explore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e00515555f4dac3c63fecb6c1de5669
https://doi.org/10.1101/2022.11.28.22279153
https://doi.org/10.1101/2022.11.28.22279153