Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Konstantia Zarkogianni"'
Autor:
Konstantia Zarkogianni, Edmund Dervakos, George Filandrianos, Theofanis Ganitidis, Vasiliki Gkatzou, Aikaterini Sakagianni, Raghu Raghavendra, C. L. Max Nikias, Giorgos Stamou, Konstantina S. Nikita
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-19 (2023)
Abstract Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest espec
Externí odkaz:
https://doaj.org/article/3aa9f5588b734923acf1fc8d3ed0b086
Autor:
Evi Chatzidaki, Vassiliki Chioti, Lidia Mourtou, Georgia Papavasileiou, Rosa-Anna Kitani, Eleftherios Kalafatis, Kostas Mitsis, Maria Athanasiou, Konstantia Zarkogianni, Konstantina Nikita, Christina Kanaka-Gantenbein, Panagiota Pervanidou
Publikováno v:
Children, Vol 11, Iss 1, p 107 (2024)
Childhood obesity is a complex disease with multiple biological and psychosocial risk factors. Recently, novel digital programs were developed with growing evidence for their effectiveness in pediatric weight management studies. The ENDORSE platform
Externí odkaz:
https://doaj.org/article/e98b01384fcd4c7993aa96d5133b8a03
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e42519 (2023)
BackgroundThe potential to harness the plurality of available data in real time along with advanced data analytics for the accurate prediction of influenza-like illness (ILI) outbreaks has gained significant scientific interest. Different methodologi
Externí odkaz:
https://doaj.org/article/0e47e053dc1f46909446e5635c6bd3d7
Autor:
Panagiota Pervanidou, Evi Chatzidaki, Nicolas C. Nicolaides, Antonis Voutetakis, Nektaria Polychronaki, Vassiliki Chioti, Rosa-Anna Kitani, Eleni Kyrkopoulou, Konstantia Zarkogianni, Eleftherios Kalafatis, Kostas Mitsis, Κonstantinos Perakis, Konstantina Nikita, Christina Kanaka-Gantenbein
Publikováno v:
Nutrients, Vol 15, Iss 7, p 1777 (2023)
Childhood obesity is a serious public health problem worldwide. The ENDORSE platform is an innovative software ecosystem based on Artificial Intelligence which consists of mobile applications for parents and health professionals, activity trackers, a
Externí odkaz:
https://doaj.org/article/103efdd962954997acb5a17e9d5ac944
Autor:
Konstantia Zarkogianni, Evi Chatzidaki, Nektaria Polychronaki, Eleftherios Kalafatis, Nicolas C. Nicolaides, Antonis Voutetakis, Vassiliki Chioti, Rosa-Anna Kitani, Kostas Mitsis, Κonstantinos Perakis, Maria Athanasiou, Danae Antonopoulou, Panagiota Pervanidou, Christina Kanaka-Gantenbein, Konstantina Nikita
Publikováno v:
Nutrients, Vol 15, Iss 6, p 1451 (2023)
Childhood obesity constitutes a major risk factor for future adverse health conditions. Multicomponent parent–child interventions are considered effective in controlling weight. Τhe ENDORSE platform utilizes m-health technologies, Artificial Intel
Externí odkaz:
https://doaj.org/article/0e1d1187bee346628d9b301765a46ddc
Autor:
Giuseppe Fico, Liss Hernanzez, Jorge Cancela, Arianna Dagliati, Lucia Sacchi, Antonio Martinez-Millana, Jorge Posada, Lidia Manero, Jose Verdú, Andrea Facchinetti, Manuel Ottaviano, Konstantia Zarkogianni, Konstantina Nikita, Leif Groop, Rafael Gabriel-Sanchez, Luca Chiovato, Vicente Traver, Juan Francisco Merino-Torres, Claudio Cobelli, Riccardo Bellazzi, Maria Teresa Arredondo
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 19, Iss 1, Pp 1-16 (2019)
Abstract Background To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. Metho
Externí odkaz:
https://doaj.org/article/d5717cd38eba4b43b06e21eec3b3bfdb
Autor:
Konstantinos Mitsis, Konstantia Zarkogianni, Eleftherios Kalafatis, Kalliopi Dalakleidi, Amyn Jaafar, Georgios Mourkousis, Konstantina S. Nikita
Publikováno v:
Sensors, Vol 22, Iss 7, p 2472 (2022)
In this article, an unobtrusive and affordable sensor-based multimodal approach for real time recognition of engagement in serious games (SGs) for health is presented. This approach aims to achieve individualization in SGs that promote self-health ma
Externí odkaz:
https://doaj.org/article/9a12cdcf4ee447f0aae03d9070b07cbc
Autor:
Eleftherios Kalafatis, Konstantinos Mitsis, Konstantia Zarkogianni, Maria Athanasiou, Antonis Voutetakis, Nicolas Nicolaides, Evi Chatzidaki, Nektaria Polychronaki, Vassia Chioti, Panagiota Pervanidou, Konstantinos Perakis, Danae Antonopoulou, Efi Papachristou, Christina Kanaka-Gantenbein, Konstantina S. Nikita
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783031320286
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a5bc6e5c7f704d69b478a77a10644e2
https://doi.org/10.1007/978-3-031-32029-3_19
https://doi.org/10.1007/978-3-031-32029-3_19
BACKGROUND The potential of harnessing the plurality of available data in real time along with advanced data analytics towards the accurate prediction of influenza-like-illness (ILI) outbreaks has gained significant scientific interest. Different met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a158dc6e6f04b298cc4d31620637d2b5
https://doi.org/10.2196/preprints.42519
https://doi.org/10.2196/preprints.42519
Publikováno v:
2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE).