ПРОГНОЗИРОВАНИЕ И ЛЕЧЕНИЕ ТРОМБОЭМБОЛИИ ЛЕГОЧНОЙ АРТЕРИИБАБУШКИНА, Г.В.,
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Geneva для прогнозирования ТЭЛА на этапе приемного отделения стационаров.
Yalaev, Bulat,
Tyurin, Anton,
Prokopenko, Inga,
Karunas, Aleksandra,
Khusnutdinova, Elza,
Khusainova, Rita (2022) . Using the polygenic
score (PGS) approach, we combined the effects of bone mineral density (BMD) DNA loci
Timasheva, Yanina,
Kochetova, Olga,
Balkhiyarova, Zhanna,
Korytina, Gulnaz,
Prokopenko, Inga,
Nouwen, Arie (2025) , we evaluated the prognostic capability of a polygenic
score model for MetS risk, both independently
Timasheva, Y.,
Balkhiyarova, Z.,
Avzaletdinova, D.,
Rassoleeva, I.,
Morugova, T.V.,
Korytina, G.,
Prokopenko, I.,
Kochetova, O. (2023) ability of the model containing polygenic
scores for the variants associated with T2D in our dataset
Savelieva, Olga,
Karunas, Alexandra,
Prokopenko, Inga,
Balkhiyarova, Zhanna,
Gilyazova, Irina,
Khidiyatova, Irina,
Khusnutdinova, Elza (2025) by genetic variability. The polygenic
score (PGS) approach enables an individual risk of asthma
Ivanova, E.,
Gilyazova, I.,
Pavlov, V.,
Izmailov, A.,
Gimalova, G.,
Karunas, A.,
Prokopenko, I.,
Khusnutdinova, E. (2022) The polygenic
scores (PGSs) are developed to help clinicians in distinguishing individuals at high