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Application of radiomics in osteoporosis detection — current capabilities and future prospects (a review)
Chugaev A., Vasilev Y., Petraikin A., Blokhin I., Vladzymyrskyy A., Omelyanskaya O.
Category PI-RADS 3: the role of texture analysis in prostate cancer risk stratification (a systematic review)
Tyan A., Kаrmаzаnovsky G., Karelskaya N., Kondratyev E., Gritskevich A., Kalinin D., Kovalev A., Baeva A.
SWOT-analysis: Remote monitoring of blood pressure
Demkina A., Korobeynikova A., Rogoza A., Vladzimirskiy A.
Use of radiomics and dosiomics to identify predictors of radiation induced lung injury
Nudnov N., Sotnikov V., Ivannikov M., Shakhvalieva E., Borisov A., Ledenev V., Smyslov A., Ananina A.
Potential use of radiomics analysis of cine-mode cardiac MRI to detect post-infarction lesions in the left ventricular myocardium
Maksimova A., Samatov D., Merzlikin B., Shelkovnikova T., Listratov A., Zavadovsky K.
Texture analysis and radiomics in the diagnosis of multiple sclerosis: a review
Khvastochenko G., Bryukhov V., Krotenkova M.
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., Tarbaeva N., Buryakina S., Kovalevich L., Khairieva A., Urusova L., Pachuashvili N., Mel'nichenko G., Mokrysheva N., Sinitsyn V.
Prediction of the efficacy of neoadjuvant chemoradiotherapy in patients with rectal cancer based on a texture analysis of T2-weighted magnetic resonance tumor image obtained at primary staging
Dayneko Y., Berezovskaya T., Mirzeabasov O., Starkov S., Myalina S., Nevolskikh A., Ivanov S., Kaprin A.
Challenges and benefits of using texture analysis of computed tomography and magnetic resonance imaging scans in diagnosis of bladder cancer
Kovalenko A., Sinitsyn V., Petrovichev V.
Artificial intelligence in ultrasound of thyroid nodules, prognosis of I-131 uptake
Manaev A., Trukhin A., Zakharova S., Sheremeta M., Troshina E.
Dosiomics in the analysis of medical images and prospects for its use in clinical practice
Solodkiy V., Nudnov N., Ivannikov M., Shakhvalieva E., Sotnikov V., Smyslov A.
A chat-bot in rheumatoid arthritis treatment control
Prokofeva Y., Zheleznykh E., Menshikova I.
Assessment of chewing efficiency with artificial intelligence
Levashov N., Gus’kov A., Oleynikov A., Domashkevich N.
The experience of using artificial intelligence for automated analysis of digital radiographs in a city hospital
Borodulin B., Gogoberidze Y., Zhilinskaya K., Prosvirkin I., Sabitov R.
Automated assessment of facial nerve dysfunction
Dembovskiy M., Boiko A.
Radiomics for diagnosing clinically significant prostate cancer PI-RADS 3: what is already known and what to do next?
Tyan A., Karmazanovskij G., Karelskaya N., Kondratyev E., Kovalev A.
Hypothesis testing using R
Blokhin I., Kodenko M., Shumskaya Y., Gonchar A., Reshetnikov R.
Radiomics in the differential diagnosis of gastrointestinal stromal tumors and leiomyomas. A literature review
Martirosyan E., Karmazanovsky G., Kondratyev E., Sokolova E.
MRI evaluation of the neoadjuvant chemoradiation therapy result in a patient with rectal cancer, supplemented with T2-WI texture analysis of the tumor: a clinical case
Dayneko Y., Berezovskaya T., Myalina S., Orekhov I., Nevolskikh 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.
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