Zobrazeno 1 - 10
of 29
pro vyhledávání: '"VAHID FARRAHI"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background Traditionally, existing studies assessing the health associations of accelerometer-measured movement behaviors have been performed with few averaged values, mainly representing the duration of physical activities and sedentary beh
Externí odkaz:
https://doaj.org/article/409caaf3c7794d5fbcae4b34c0a6aad2
Autor:
Laura Nauha, Vahid Farrahi, Heidi Jurvelin, Timo Jämsä, Maisa Niemelä, Maarit Kangas, Raija Korpelainen
Publikováno v:
Annals of Medicine, Vol 55, Iss 1 (2023)
AbstractObjectives Discriminating sleep period from accelerometer data remains a challenge despite many studies have adapted 24-h measurement protocols. We aimed to compare and examine the agreement among device-estimated and self-reported bedtime, w
Externí odkaz:
https://doaj.org/article/3057d82031b047feb3228231e8a92e18
Publikováno v:
IEEE Access, Vol 11, Pp 30247-30272 (2023)
Over the past few years, the number and volume of data sources in healthcare databases has grown exponentially. Analyzing these voluminous medical data is both opportunity and challenge for knowledge discovery in health informatics. In the last decad
Externí odkaz:
https://doaj.org/article/56169625936d43409f0813436fc9aa0f
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 15, Iss 1, Pp 1-24 (2022)
Abstract Food recommendation systems have been increasingly developed in online food services to make recommendations to users according to their previous diets. Although unhealthy diets may cause challenging diseases such as diabetes, cancer, and pr
Externí odkaz:
https://doaj.org/article/b1bcbd8cbff047d0a841c7708f0cfb56
Publikováno v:
IEEE Access, Vol 10, Pp 52508-52524 (2022)
Food recommender-systems are considered an effective tool to help users adjust their eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food recommender-system to overcome the shortcomings of previous systems, such as
Externí odkaz:
https://doaj.org/article/83a124bdc05441b09ae70f821d2139ec
Autor:
Mehrdad Rostami, Usman Muhammad, Saman Forouzandeh, Kamal Berahmand, Vahid Farrahi, Mourad Oussalah
Publikováno v:
Intelligent Systems with Applications, Vol 16, Iss , Pp 200157- (2022)
In food diet communication domain, images convey important information to capture users' attention beyond the traditional ingredient content, making it crucial to influence user-decision about the relevancy of a given diet. By using a deep learning-b
Externí odkaz:
https://doaj.org/article/b7400217d63d49c1b8609816c941ba48
Autor:
Vahid Farrahi, Maisa Niemelä, Mikko Kärmeniemi, Soile Puhakka, Maarit Kangas, Raija Korpelainen, Timo Jämsä
Publikováno v:
International Journal of Behavioral Nutrition and Physical Activity, Vol 17, Iss 1, Pp 1-14 (2020)
Abstract Purpose A data mining approach was applied to establish a multilevel hierarchy predicting physical activity (PA) behavior, and to methodologically identify the correlates of PA behavior. Methods Cross-sectional data from the population-based
Externí odkaz:
https://doaj.org/article/67b44416b3bf4011a2017a3b857db421
Autor:
Vahid Farrahi, Mehrdad Rostami, Laura Nauha, Maija Korpisaari, Maisa Niemelä, Timo Jämsä, Raija Korpelainen, Mourad Oussalah
Publikováno v:
Scandinavian Journal of Medicine & Science in Sports. 33:907-920
Autor:
Maisa Niemelä, Antti Kiviniemi, Tiina M. Ikäheimo, Mikko Tulppo, Raija Korpelainen, Timo Jämsä, Vahid Farrahi
Publikováno v:
Scandinavian Journal of Medicine & Science in Sports. 33:641-650
Autor:
JAANA T. KARI, IIRO NERG, SANNA HUIKARI, ANNA-MAIJU LEINONEN, MARJUKKA NURKKALA, VAHID FARRAHI, RAIJA KORPELAINEN, MARKO KORHONEN
Purpose: This study estimated the long-term individual-level productivity costs of physical inactivity. Methods: The data were drawn from the Northern Finland Birth Cohort 1966, to which the productivity cost variables (sick leaves and disability pen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e1489afc715849501b20990e69045f7b
http://urn.fi/URN:NBN:fi:jyu-202301171363
http://urn.fi/URN:NBN:fi:jyu-202301171363