По вашему запросу найдено документов: 25

Страница 1 из 3

Predicting Threat Degree for Onset of Type 2 Diabetes Mellitus Based on Machine Learning Methods
Shakhmametova, G., Vakkazov, N., Klimets, S. (2023)
classification model based on the logistic regression method has been proposed and developed. The developed
Risk Factors for Cerebral Hyperperfusion Syndrome After Combined Revascularization in Adult Patients with Moyamoya Disease
Xu, Dongxiao, Guo, Jiaojiao, Zheng, Bingjie, Wu, Qiaowei, Gareev, Ilgiz, Beylerli, Ozal, Beilerli, Aferin, Shi, Huaizhang (2023)
features were recorded. Postoperative CHS after surgery were examined. Multivariate logistic regression
Predictors of Adverse Outcomes in Ischemic Stroke Associated with COVID-19
Novikova, L.B. ;, Latypova, R.F. (2023)
outcome were studied by binary logistic regression. Results. Univariate analysis showed that the risk
ANTISOCIAL BEHAVIOR: NATURE VS. NURTURE
Kazantseva, A.V., Yakovleva, D.V., Davydova, Yu. D., Kosareva, A.R., Valinurov, R.G., Khusnutdinova, E.K. (2023)
). A series of logistic regression (PLINK v.1.09) confirmed the association of REV3L rs458806
Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes
Timasheva, Y., Balkhiyarova, Z., Avzaletdinova, D., Rassoleeva, I., Morugova, T.V., Korytina, G., Prokopenko, I., Kochetova, O. (2023)
, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis
Предикторы больничной летальности среди пациентов с инсультом, ассоциированным с новой коронавирусной инфекцией COVID-19
Predictors of In-Hospital Mortality Among Patients with COVID-19 Related Stroke
Рахматуллин, А.Р., Кутлубаев, М.А., Хайруллин, А.Т., Rakhmatullin, Airat R., Kutlubaev, Mansur A., Khayrullin, Amir T. (2023)
The potential of miR-153 as aggressive prostate cancer biomarker
Gilyazova, Irina, Ivanova, Elizaveta, Sinelnikov, Mikhail, Pavlov, Valentin, Khusnutdinova, Elza, Khusnutdinova, Elza, Beilerli, Aferin, Mikhaleva, Ludmila, Liang, Yanchao (2023)
marker (AUC = 0.85; 95%CI 0.75–0.95; sensitivity = 0.72, specificity = 0.86)). According to logistic
Host Genetic Variants Linked to COVID-19 Neurological Complications and Susceptibility in Young Adults—A Preliminary Analysis
Kazantseva, A., Enikeeva, R., Takhirova, Z., Davydova, Y., Mustafin, R., Malykh, S., Karunas, A., Kanapin, A., Khusnutdinova, E. (2023)
and neurological symptoms in anamnesis comprised the study sample. Logistic regression was performed with COVID-19
Оценка прогноза исхода тяжелой внебольничной пневмонии, вызванной Klebsiella Pneumoniae
Assessment of the prognosis of the outcome of severe community-acquired pneumonia caused by Klebsiella pneumoniae
Sakharov, Valeriy I., Mironov, Petr I., Tsandekov, Anton A., Rudnov, Vladimir A., Сахаров, В. И., Миронов, П. И., Цандеков, А. А., Руднов, В. А. (2023)
Prophylactic rivaroxaban in the early post-discharge period reduces the rates of hospitalization for atrial fibrillation and incidence of sudden cardiac death during long-term follow-up in hospitalized COVID-19 survivors
Fiedler, Lukas, Motloch, Lukas J., Dieplinger, Anna-Maria, Jirak, Peter, Davtyan, Paruir, Gareeva, Diana, Badykova, Elena, Badykov, Marat, Lakman, Irina, Agapitov, Aleksandr, Sadikova, Liana, Pavlov, Valentin, Föttinger, Fabian, Mirna, Moritz, Kopp, Kristen, Hoppe, Uta C., Pistulli, Rudin, Cai, Benzhi, Yang, Baofeng, Zagidullin, Naufal (2023)
applying a logistic regression model for propensity score matching (AF: χ2-statistics = 6.45, p = 0

Страница 1 из 3

Google Scholar
OpenDoar

Фасеты

Авторы
Ключевые слова
Год