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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.
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.
Machine learning techniques for breast cancer diagnosis
Dyomin K.S., Germashev I.V.
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.
Classification of adrenocortical carcinoma, pheochromocytoma, and adrenal adenomas using contrast-enhanced computed tomography with machine learning and texture features: a cross-sectional study
Manaev A.V., Tarbaeva N.V., Buryakina S.A., Kovalevich L.D., Khairieva A.V., Urusova L.S., Pachuashvili N.V., Mel'nichenko G.A., Mokrysheva N.G., Sinitsyn V.E.
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.
Use of artificial intelligence technologies in laboratory medicine, their effectiveness and application scenarios: a systematic review
Vasilev Y.A., Nanova O.G., Vladzymyrskyy A.V., Goldberg A.S., Blokhin I.A., Reshetnikov R.V.
Assessment of ovarian follicular reserve according to ultrasound data based on machine learning methods
Laputin F.A., Sidorov I.V., Moshkin A.S.
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.
Learning radiologists’ annotation styles with multi-annotator labeling for improved neural network performance
Nikitin E.D.
Digital technologies and artificial intelligence in the diagnosis of cardiovascular complications in pregnancy: a review
Trusov Y.A., Shamsueva K.T., Kolkhidova M.Z., Inderbieva A.T., Baryshnikova E.D., Khusnutdinova K.A., Rasponomareva A.E., Shabazgerieva A.R., Radzhabov K.K., Sanakoev S.A., Kudzieva V.K., Ponomareva A.V., Kozyreva N.K.
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.
Digital diagnostics: A computer application for lymph node metastases in cervical cancer
Kuznetsov A.I.
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.
The concept of responsible artificial intelligence as the future of artificial intelligence in medicine
Germanov N.S.
Role of artificial intelligence and novel visualization techniques in the early diagnosis of pancreatic cancer: a review
Musaeva F.T., Sumenova E.R., Islamgulov A.K., Kumykova Z.M., Elipkhanova T.S., Ushaeva A.I., Khasieva A.S., Ozerova E.S., Khusnutdinova D.A., Nabiullina A.A., Kulinskaya Y.Y., Yakupova R.R., Mustafin A.A.
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.
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.
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.
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.
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.
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.
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.
Machine-learning technology for predicting intraocular lens power: Diagnostic data generalization
Arzamastsev A.А., Fabrikantov O.L., Zenkova N.А., Belikov S.V.
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.
Classification of optical coherence tomography images using deep machine-learning methods
Arzamastsev A.A., Fabrikantov O.L., Kulagina E.V., Zenkova N.A.
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.
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