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Title
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No 10 (2023)
Development and validation of models to predict total and early-onset preeclampsia in the first trimester of pregnancy using machine learning algorithms
Andreychenko A.E., Luchinin A.S., Ivshin A.A., Ermak A.D., Novitskiy R.E., Gusev A.V.
PDF
(Rus)
No 2 (2024)
Comparison of predictive models built with different machine learning techniques using the example of predicting the outcome of assisted reproductive technologies
Drapkina Y.S., Makarova N.P., Vasiliev R.A., Amelin V.V., Kalinina E.A.
PDF
(Rus)
No 3 (2024)
Application of various machine learning techniques to the analysis of clinical, anamnestic, and embryological data of patients undergoing assisted reproductive technologies
Drapkina Y.S., Makarova N.P., Vasiliev R.A., Amelin V.V., Frankevich V.E., Kalinina E.A.
PDF
(Rus)
No 5 (2021)
Artificial intelligence on guard of reproductive health
Ivshin A.A., Bagaudin T.Z., Gusev A.V.
PDF
(Rus)
No 7 (2020)
Enhancing the efficiency of assisted reproductive technologies using artificial intelligence and machine learning at the embryological stage
Sysoeva A.P., Makarova N.P., Kalinina E.A., Skibina J.S., Zanishevskaya A.A., Yanchuk N.O., Gryaznov A.Y.
PDF
(Rus)
No 11 (2022)
Artificial intelligence in reproductive medicine: ethical and clinical aspects
Drapkina Y.S., Kalinina E.A., Makarova N.P., Milchakov K.S., Frankevich V.E.
PDF
(Rus)
No 12 (2022)
Search for the predictors of fetal growth restriction: from a measuring tape to artificial intellect
Gumeniuk E.G., Ivshin A.A., Boldina Y.S.
PDF
(Rus)
No 2 (2021)
THE STATE OF AND PROSPECTS FOR THE INTRODUCTION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN OBSTETRIC AND GYNECOLOGICAL PRACTICE
Sukhikh G.T., Davydov D.G., Loginov V.V., Baev O.R., Prikhodko A.M., Sheshko E.L., Chmykhova E.V.
PDF
(Rus)
1 - 8 of 8 Items

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