Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Bálint Daróczy"'
Autor:
Beáta Kovács, Ákos Németh, Bálint Daróczy, Zsolt Karányi, László Maroda, Ágnes Diószegi, Bíborka Nádró, Tamás Szabó, Mariann Harangi, Dénes Páll
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 9 (2023)
ObjectiveIdentifying hypertension in children and providing treatment for it have a marked impact on the patients’ long-term cardiovascular outcomes. The global prevalence of childhood hypertension is increasing, yet its investigation has been rath
Externí odkaz:
https://doaj.org/article/870b5264bd074f799d32f03e6bf682de
Autor:
Beáta Kovács, Ákos Németh, Bálint Daróczy, Zsolt Karányi, László Maroda, Ágnes Diószegi, Mariann Harangi, Dénes Páll
Publikováno v:
Journal of Cardiovascular Development and Disease, Vol 10, Iss 8, p 345 (2023)
Cardiovascular diseases are among the leading causes of mortality worldwide. Hypertension is a preventable risk factor leading to major cardiovascular events. We have not found a comprehensive study investigating Central and Eastern European hyperten
Externí odkaz:
https://doaj.org/article/a86c6813dfa942a1868aca09f752a155
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Background and aims: Premature mortality due to atherosclerotic vascular disease is very high in Hungary in comparison with international prevalence rates, though the estimated prevalence of familial hypercholesterolemia (FH) is in line with the data
Externí odkaz:
https://doaj.org/article/ed0bfa2b47614f778bbb93e336f22547
Autor:
Bálint Daróczy
Publikováno v:
Mathematics, Vol 10, Iss 7, p 1123 (2022)
Recent articles indicate that deep neural networks are efficient models for various learning problems. However, they are often highly sensitive to various changes that cannot be detected by an independent observer. As our understanding of deep neural
Externí odkaz:
https://doaj.org/article/910087b9d313424a817904f068c7e7f9
Publikováno v:
Agronomy, Vol 12, Iss 2, p 395 (2022)
To better understand the potential of soils, understanding how soil properties vary over time and in-field is essential to optimize the cultivation and site-specific technologies in crop production. This article aimed at determining the within-field
Externí odkaz:
https://doaj.org/article/0f7b2bf0f5844aeaa148c82060c37435
Publikováno v:
Sensors, Vol 19, Iss 16, p 3498 (2019)
Recommendation services bear great importance in e-commerce, shopping, tourism, and social media, as they aid the user in navigating through the items that are most relevant to their needs. In order to build recommender systems, organizations log the
Externí odkaz:
https://doaj.org/article/5ad2b3b2cfb24c50b648471d3176d1ad
Machine learning methods are frequently used to detect behavioral and ecological data patterns. Even though these new mathematical methods are useful tools, the results are often ambivalent if we do not utilize biologically relevant parameters in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c11432e44eba62f5ce345820209c83a5
https://doi.org/10.21203/rs.3.rs-2185125/v1
https://doi.org/10.21203/rs.3.rs-2185125/v1
Publikováno v:
Journal of Clinical Medicine; Volume 11; Issue 15; Pages: 4311
Background: There are no exact data about the prevalence of familial chylomicronemia syndrome (FCS) in Central Europe. We aimed to identify FCS patients using either the FCS score proposed by Moulin et al. or with data mining, and assessed the diagno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::699d3735b1b2e223b0acff00b5210f76
Publikováno v:
Journal of clinical medicine. 11(15)
There are no exact data about the prevalence of familial chylomicronemia syndrome (FCS) in Central Europe. We aimed to identify FCS patients using either the FCS score proposed by Moulin et al. or with data mining, and assessed the diagnostic applica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::fe8829db8efebf185203167f30bfaa70
https://pubmed.ncbi.nlm.nih.gov/35893402
https://pubmed.ncbi.nlm.nih.gov/35893402
Autor:
Antal Hiba, Akos Zarandy, András A. Benczúr, Péter Bauer, Koppány Pázmán, Rita Aleksziev, Bálint Daróczy
Publikováno v:
IFAC-PapersOnLine. 52:7-12
Contextual calibration for object detection is a technique where a pretrained network collects attractive false positives during a calibration phase and use this calibration data for further training. This paper investigates the applicability of this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33c9c0e4c4db0665c17a3add8942adf9
https://doi.org/10.1016/j.ifacol.2019.09.110
https://doi.org/10.1016/j.ifacol.2019.09.110