Іздеу

Шығарылым
Атауы
Авторлар
Use of artificial intelligence technologies in laboratory medicine, their effectiveness and application scenarios: a systematic review
Vasilev Y., Nanova O., Vladzymyrskyy A., Goldberg A., Blokhin I., Reshetnikov R.
Assessment of ovarian follicular reserve according to ultrasound data based on machine learning methods
Laputin F., Sidorov I., Moshkin A.
Modern capabilities of artificial intelligence technologies in cardiovascular imaging
Islamgulov A., Bogdanova A., Sufiiarov D., Chernyavskaya A., Bairakaeva E., Maksimova A., Nemychnikov N., Bikieva D., Shakhmaeva A., Burdina L., Bolekhan A., Akimov E., Shurakova Z.
Prospects of machine learning applications in affective disorders
Mosolova E., Alfimov A., Kostyukova E., Mosolov S.
Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review
Kryuchkova O., Schepkina E., Rubtsova N., Alekseev B., Kuznetsov A., Epifanova S., Zarya E., Talyshinskii A.
Use of artificial intelligence in the diagnosis of arterial calcification
Trusov Y., Chupakhina V., Nurkaeva A., Yakovenko N., Ablenina I., Latypova R., Pitke A., Yazovskih A., Ivanov A., Bogatyreva D., Popova U., Yuzlekbaev A.
Reference medical datasets (MosMedData) for independent external evaluation of algorithms based on artificial intelligence in diagnostics
Pavlov N., Andreychenko A., Vladzymyrskyy A., Revazyan A., Kirpichev Y., Morozov 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., Vladzymyrskyy A., Arzamasov K., Shikhmuradov D., Pankratov A., Ulyanov I., Nechaev N.
MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic
Morozov S., Andreychenko A., Blokhin I., Gelezhe P., Gonchar A., Nikolaev A., Pavlov N., Chernina V., Gombolevskiy V.
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.
Learning radiologists’ annotation styles with multi-annotator labeling for improved neural network performance
Nikitin E.
Artificial intelligence in ultrasound of thyroid nodules, prognosis of I-131 uptake
Manaev A., Trukhin A., Zakharova S., Sheremeta M., Troshina E.
Digital diagnostics: A computer application for lymph node metastases in cervical cancer
Kuznetsov A.
Machine learning techniques for breast cancer diagnosis
Dyomin K., Germashev I.
The concept of responsible artificial intelligence as the future of artificial intelligence in medicine
Germanov N.
Machine-learning and artificial neural network technologies in the classification of postkeratotomic corneal deformity
Tsyrenzhapova E., Rozanova O., Iureva T., Ivanov A., Rozanov I.
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.
Radiomics in application to diseases of the musculoskeletal system: a review
Pleshkov M., Zamyshevskaya M., Kuchinskii E., Jin X., Zhang J., Zavadovskaya V., Zorkaltsev M., Kim T., Pogonchenkova D., Udodov V., Tolmachev I.
Machine-learning technology for predicting intraocular lens power: Diagnostic data generalization
Arzamastsev A., Fabrikantov O., Zenkova N., Belikov S.
Evolution of research and development in the field of artificial intelligence technologies for healthcare in the Russian Federation: results of 2021
Gusev A., Vladzymyrskyy A., Sharova D., Arzamasov K., Khramov A.
Predicting atrial fibrillation in comorbid patients with arterial hypertension and chronic obstructive pulmonary disease using laboratory research methods: a machine learning approach
Kazantseva E., Ivannikov A., Tarzimanova A., Podzolkov V.
Classification of optical coherence tomography images using deep machine-learning methods
Arzamastsev A., Fabrikantov O., Kulagina E., Zenkova N.
Does aggregating results of AI system for mammography with ML meta-model improve quality of malignancy detection?
Nikitin E.
Нәтижелер 23 - 1/23
Сыбырсөздер:
  • Негізгі сөздер тіркелімге сезімтал< / li>
  • Ағылшын предлогтары мен одақтары еленбейді
  • Әдепкі бойынша іздеу барлық негізгі сөздер үшін жасалады (агенс AND экспериенцер)
  • Белгілі бір терминді табу үшін OR қолданыңыз. білім беру OR оқыту
  • мысалы, күрделі сөз тіркестерін жасау үшін жақшаларды қолданыңыз. мұрағат ((журналдар OR конференциялар) NOT диссертациялар)
  • Нақты фразаны табу үшін, мысалы, тырнақшаларды қолданыңыз. "ғылыми зерттеулер"
  • сөзді - (сызықша) немесе not операторының көмегімен алып тастаңыз; мысалы. сұлулық байқауы< / em > немесе сұлулық байқауы< / em > < / li>
  • мысалы, нұсқа ретінде * қолданыңыз. ғылым* "ғылыми","ғылыми"және т. б. сөздерді қамтиды< / li> < / < / к-сі>