По вашему запросу найдено документов: 19

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Machine Learning Methods and Models for Recognizing Lung Inhomogeneity from Computed Tomography Scans
Shakhmametova, G. R., Stepanova, E. S., Akhmetshin, A. A., Zulkarneev, R. Kh. (2023)
The article considers the use of deep neural networks for the recognition of lungs inhomogeneity
Прогнозирование клинически узкого таза с помощью нейросетевого анализа данных
Predicting a clinically narrow pelvis using neural network data analysis
Ziganshin, Aydar M., Dikke, Galina B., Mudrov, Viсtor A., Зиганшин, А.М., Дикке, Г.Б., Мудров, В.А. (2023)
модуля Neural Networks программы SPSS Statistics Version 25.0 (IBM, США). Результаты. Несмотря на
Использование методов машинного обучения в диагностике и прогнозировании клинических особенностей шизофрении: нарративный обзор литературы
Machine Learning Techniques in Diagnostics and Prediction of the Clinical Features of Schizophrenia: A Narrative Review
Gashkarimov, Vadim Rimovich, Sultanova, Renata Ildarovna, Efremov, Ilya Segeevich, Asadullin, Azat (2023)
”, “neural network”, “predictors”, “artificial intelligence”, “diagnostics”, “suicide”, “depressive
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)
A roadmap for research in post-stroke fatigue: Consensus-based core recommendations from the third Stroke Recovery and Rehabilitation Roundtable
English, Coralie, Simpson, Dawn B, Billinger, Sandra A, Churilov, Leonid, Coupland, Kirsten G, Drummond, Avril, Kuppuswamy, Annapoorna, Kutlubaev, Mansur A., Lerdal, Anners., Mahmood, Amreen, Moseley, G Lorimer, Pittman, Quentin J, Riley, Ellyn A., Riley, Ellyn A., Wong, Connie HY., Corbett, Dale, Mead, Gillian (2023)
Development of Data Storage and User Interface in the Clinical Decision Support System
Shakhmametova, G.R., Evgrafov, A.A., Zulkarneev, R. Kh. (2023)
Predicting Threat Degree for Onset of Type 2 Diabetes Mellitus Based on Machine Learning Methods
Shakhmametova, G., Vakkazov, N., Klimets, S. (2023)
The function of miRNAs in the process of kidney development
Sun, Pengfei, Wang, Jiaqi, Ilyasova, Tatiana, Shumadalova, Alina, Agaverdiev, Murad, Wang, Chunlei (2023)
RNAs have emerged as key players in this pathological process. By shedding light on the intricate network
Perspective for Studying the Relationship of miRNAs with Transposable Elements
Mustafin, R.N., Khusnutdinova, E. (2023)
NC-TE), which can be used to design epigenetic gene networks in ontogenesis. Based on the data accumulated
The Concept of a Decision Support System in the Management of Treatment and Accompaniment of the Patient with Bronchopulmonary Diseases
Bogdanova, D.R., Yusupova, N.I., Zulkarneev, RKh (2023)

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