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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
Noether symmetries, group analysis and soliton solutions of a (3+1)-dimensional generalized fifth-order Zakharov–Kuznetsov model with power, dual power laws and dispersed perturbation terms with real-world applications
Adeyemo, Oke Davies, Khalique, Chaudry Masood, Migranov, Nail G. (2024)
the newly introduced logistic function technique for some particular cases of the equation under
Маршрутизация и логистика больных туберкулезом легких при отборе на хирургическое лечение в Республике Башкортостан
Routing and Logistics of Pulmonary Tuberculosis Patients During Selection for Surgical Treatment in the Republic of Bashkortostan
Сабирова, А.Р., Шарипов, Р.А., Тукфатуллин, Р.К., Азаматова, М.М., Sabirova, Adilya R., Sharipov, Raul A., Tukfatullin, Ravil K., Azamatova, Mininur M. (№4, 2023)
Routing and Logistics of Pulmonary Tuberculosis Patients During Selection for Surgical Treatment
Сравнительная оценка прогностической способности шкал органной дисфункции paediatric Sequential Organ Failure Assessment (pSOFA), paediatric logistic organ dysfunction 2 (PELOD 2) и оценочной системы Vasoactive-Inotropic Score (VIS) у детей с септическим шоком: ретроспективное наблюдательное исследование
Comparative assessment of the prognostic ability of paediatric Sequential Organ Failure Assessment (pSOFA), paediatric logistic organ dysfunction 2 (PELOD 2) and Vasoactive-Inotropic Score (VIS) in children with septic shock: a retrospective observational study
Trembach, А.V., Bgane, N.M., Trembach, I.A., Mironov, P.I., Аleksandrovich, Yu.S., Трембач, А. В., Бгане, Н. М., Трембач, И. А., Миронов, П. И., Александрович, Ю. С. (2024)
(pSOFA), paediatric logistic organ dysfunction 2 (PELOD 2) and Vasoactive-Inotropic Score (VIS
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
Polygenic Score Approach to Predicting Risk of Metabolic Syndrome
Timasheva, Yanina, Kochetova, Olga, Balkhiyarova, Zhanna, Korytina, Gulnaz, Prokopenko, Inga, Nouwen, Arie (2025)
variants across these pathways in 279 MetS patients and 397 healthy individuals. Using logistic regression
ЛОГИСТИКА ЛИМФОГЕННОГО МЕТАСТАЗИРОВАНИЯ ПРИ РАКЕ МОЛОЧНОЙ ЖЕЛЕЗЫ
LOGISTICS OF LYMPHOGENIC BREAST CANCER METASTASIS
Ш. Х. Ганцев, Sh. Kh. Gantsev, К. Умезава, K. Umezawa, А. В. Султанбаев, A. V. Sultanbaev, Р. Ш. Ишмуратова, R. Sh. Ishmuratova, В. Ю. Фролова, V. Yu. Frolova, А. Т. Ахметов, A. T. Akhmetov, Э. А. Фазлыева, E. А. Fazlyeva, Ш. Р. Кзыргалин, Sh. R. Kzyrgalin (Креативная хирургия и онкология, №2, 2017)
LOGISTICS OF LYMPHOGENIC BREAST CANCER METASTASIS
LEFT VENTRICULAR EJECTION FRACTION AS AN INDEPENDENT PREDICTOR OF POOR OUTCOME IN ACUTE INTRACEREBRAL HEMORRHAGE
YANG, G., SUN, J., ZHANG, D., ZHANG, R., ZHONG, Y., WANG, X., CHEN, X., LIU, B., LI, L., ZHAO, S., WANG, L., YUAN, C., LONG, M., JIANG, H., LI, C., ZHOU, Q., LIAN, A., GAREEV, I. (2020)
were investigated using univariable and multivariable logistic regression models. Results: Depressed
ПРОГНОЗИРОВАНИЕ РЕЗУЛЬТАТОВ ЛЕЧЕНИЯ ПЕРВИЧНОГО ПУЗЫРНО-МОЧЕТОЧНИКОВОГО РЕФЛЮКСА У ДЕТЕЙ
PREDICTING THE RESULTS OF TREATMENT OF PRIMARY VESICOURETERAL REFLUX IN CHILDREN
Зоркин, С.Н., Гурская, А.С., Баязитов, Р.Р., Шахновский, Д.С., Zorkin, S.N., Gurskaya, A.S., Baiazitov, R.R., Shakhnovskiy, D.S. (2022)
PREVALENCE AND RISK FACTORS FOR ERECTILE DYSFUNCTION AND LOWER URINARY TRACT SYMPTOMS IN RUSSIAN FEDERATION MEN: ANALYSIS FROM A NATIONAL POPULATION-BASED MULTICENTER STUDY
Korneyev, I.A., Alexeeva, T.A., Al-Shukri, S.H., Bernikov, A.N., Erkovich, A.A., Kamalov, A.A., Kogan, M.I., Pavlov, V.N., Zhuravlev, V.N., Pushkar, D.Y. (2016)
-adjusted odds ratio between 1.2 and 5.2. In logistic regression model (R2=0.361), the strongest associated

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