The possible role of machine learning in detection of increased cardiovascular risk patients – KSC MR Study (design)

INTRODUCTION: Currently, just a few major parameters are used for cardiovascular (CV) risk quantification to identify many of the high-risk subjects; however, they leave a lot of them with an underestimated level of CV risk which does not reflect the reality. MATERIAL AND METHODS: The submitted stud...

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Detalles Bibliográficos
Autores principales: Pella, Daniel, Toth, Stefan, Paralic, Jan, Gonsorcik, Jozef, Fedacko, Jan, Jarcuska, Peter, Pella, Dominik, Pella, Zuzana, Sabol, Frantisek, Jankajova, Monika, Valocik, Gabriel, Putrya, Alina, Kirschová, Andrea, Plachy, Lukas, Rabajdova, Miroslava, Hunavy, Mikulas, Kafkova, Bibiana, Doci, Ivan, Timkova, Silvia, Dvorožňáková, Mariana, Babic, Frantisek, Butka, Peter, Dimunova, Lucia, Marekova, Maria, Paralicova, Zuzana, Majernik, Jaroslav, Luczy, Jan, Janosik, Jakub, Kmec, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2020
Materias:
Clinical Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266729/
https://www.ncbi.nlm.nih.gov/pubmed/35832722
http://dx.doi.org/10.5114/aoms.2020.99156

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266729/
https://www.ncbi.nlm.nih.gov/pubmed/35832722
http://dx.doi.org/10.5114/aoms.2020.99156

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