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Assessment of ovarian follicular reserve according to ultrasound data based on machine learning methods
Laputin F.A., Sidorov I.V., Moshkin A.S.
Prospects of machine learning applications in affective disorders
Mosolova E.S., Alfimov A.E., Kostyukova E.G., Mosolov S.N.
Modern capabilities of artificial intelligence technologies in cardiovascular imaging
Islamgulov A.K., Bogdanova A.S., Sufiiarov D.I., Chernyavskaya A.V., Bairakaeva E.R., Maksimova A.A., Nemychnikov N.V., Bikieva D.R., Shakhmaeva A.I., Burdina L.A., Bolekhan A.V., Akimov E.I., Shurakova Z.Z.
Classification of optical coherence tomography images using deep machine-learning methods
Arzamastsev A.A., Fabrikantov O.L., Kulagina E.V., Zenkova N.A.
Evolution of research and development in the field of artificial intelligence technologies for healthcare in the Russian Federation: results of 2021
Gusev A.V., Vladzymyrskyy A.V., Sharova D.E., Arzamasov K.M., Khramov A.E.
Classification of the presence of malignant lesions on mammogram using deep learning
Ibragimov A.A., Senotrusova S.A., Litvinov A.A., Beliaeva A.A., Ushakov E.N., Markin Y.V.
Use of artificial intelligence in the diagnosis of arterial calcification
Trusov Y.А., Chupakhina V.S., Nurkaeva A.S., Yakovenko N.A., Ablenina I.V., Latypova R.F., Pitke A.P., Yazovskih A.A., Ivanov A.S., Bogatyreva D.S., Popova U.A., Yuzlekbaev A.F.
Reference medical datasets (MosMedData) for independent external evaluation of algorithms based on artificial intelligence in diagnostics
Pavlov N.A., Andreychenko A.E., Vladzymyrskyy A.V., Revazyan A.A., Kirpichev Y.S., Morozov S.P.
Using neural networks for non-invasive determination of glycated hemoglobin levels, illustrated by the application of an innovative portable glucometer in clinical practice
Poliker E.E., Koshechkin K.A., Timokhin A.M., Klyukina E.V., Belyakova E.D., Brovko A.M., Lalayan A.S., Ermolaeva A.S.
Prospects of using computer vision technology to detect urinary stones and liver and kidney neoplasms on computed tomography images of the abdomen and retroperitoneal space
Vasilev Y.A., Vladzymyrskyy A.V., Arzamasov K.M., Shikhmuradov D.U., Pankratov A.V., Ulyanov I.V., Nechaev N.B.
Students opinion about E-Learning in a Master course in Interventional Radiology: a survey among participants
Neri E., Crocetti L., Lorenzoni G., Cioni R., Brady A., Caramella D.
Radiomics in application to diseases of the musculoskeletal system: a review
Pleshkov M.O., Zamyshevskaya M.A., Kuchinskii E.V., Jin X., Zhang J., Zavadovskaya V.D., Zorkaltsev M.A., Kim T.V., Pogonchenkova D.A., Udodov V.D., Tolmachev I.V.
Predicting atrial fibrillation in comorbid patients with arterial hypertension and chronic obstructive pulmonary disease using laboratory research methods: a machine learning approach
Kazantseva E.V., Ivannikov A.A., Tarzimanova A.I., Podzolkov V.I.
Dosiomics in the analysis of medical images and prospects for its use in clinical practice
Solodkiy V.A., Nudnov N.V., Ivannikov M.E., Shakhvalieva E.S., Sotnikov V.M., Smyslov A.Y.
MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic
Morozov S.P., Andreychenko A.E., Blokhin I.A., Gelezhe P.B., Gonchar A.P., Nikolaev A.E., Pavlov N.A., Chernina V.Y., Gombolevskiy V.A.
Development of a prognostic model for diagnosis of prostate cancer based on radiomics of biparametric magnetic resonance imaging apparent diffusion coefficient maps and stacking of machine learning algorithms
Kuznetsov A.I.
Development of a portable spectrophotometer using artificial neural networks for non-invasive determination of glycated hemoglobin in blood by Raman spectroscopy
Poliker E.E., Zemskikh B.L., Koshechkin K.A.
Machine learning techniques for breast cancer diagnosis
Dyomin K.S., Germashev I.V.
Artificial intelligence in ultrasound of thyroid nodules, prognosis of I-131 uptake
Manaev A.V., Trukhin A.A., Zakharova S.M., Sheremeta M.S., Troshina E.A.
Learning radiologists’ annotation styles with multi-annotator labeling for improved neural network performance
Nikitin E.D.
Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review
Kryuchkova O.V., Schepkina E.V., Rubtsova N.A., Alekseev B.Y., Kuznetsov A.I., Epifanova S.V., Zarya E.V., Talyshinskii A.E.
Machine-learning technology for predicting intraocular lens power: Diagnostic data generalization
Arzamastsev A.А., Fabrikantov O.L., Zenkova N.А., Belikov S.V.
Digital diagnostics: A computer application for lymph node metastases in cervical cancer
Kuznetsov A.I.
Assessing the probability of metastatic mediastinal lymph node involvement in patients with non-small cell lung cancer using convolutional neural networks on chest computed tomography
Shevtsov A.E., Tominin I.D., Tominin V.D., Malevanniy V.M., Esakov Y.S., Tukvadze Z.G., Nefedov A.O., Yablonskii P.K., Gavrilov P.V., Kozlov V.V., Blokhina M.E., Nalivkina E.A., Gombolevskiy V.A., Vasilev Y.A., Dugova M.N., Chernina V.Y., Omelyanskaya O.V., Reshetnikov R.V., Blokhin I.A., Belyaev M.G.
Machine-learning and artificial neural network technologies in the classification of postkeratotomic corneal deformity
Tsyrenzhapova E.K., Rozanova O.I., Iureva T.N., Ivanov A.A., Rozanov I.S.
The concept of responsible artificial intelligence as the future of artificial intelligence in medicine
Germanov N.S.
1 - 26 of 26 Items

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