Chomakhidze P Sh - IM Sechenov First Moscow State Med Univ, Sechenov Univ

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论文共 46 篇作者统计合作学者相似作者

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Determining The Risk of Atrial Fibrillation Paroxysm in Patients With Chronic Heart Failure With Intact and Reduced Ejection Fraction

I P Zakharov,P Sh Chomakhidze,F Yu Kopylov, E A Sultygova, D F Mesitskaya, E A Lyubimova, D A Andreev

Kardiologiia（2024）

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[Remote Monitoring of the QT Interval During Polychemotherapy]

Z Z A Fashafsha,P Sh Chomakhidze, D F Mesitskaya, A I Novikova, N A Potemkina,A Yu Suvorov, E S Tyukanova, A S Fatyanova,Yu S Agakina, M I Sekacheva, E V Poddubskaya,Ph Yu Kopylov

Kardiologiia（2023）

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Comparison of ct angiography and scoring systems for cardiovascular risk stratification in asymptomatic patients

Andrey N. Rozhkov,Dmitry Shchekochikhin, Ekaterina S. Tebenkova, Е. А. Сыркина,Daria Gognieva, A.S. Akselrod,П. Ш. Чомахидзе, Philipp Kopylov, Д. С. Тутер

Kardiologiya i serdechno-sosudistaya khirurgiyano. 2 (2023): 190-190

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Incidence of atrial fibrillation paroxysms in chronic heart failure patients with preserved and reduced ejection fraction

I.P. Zakharov, A.I. Borenstein,N.O. Kuznetsova,V.P. Sedov,Ph.Yu. Kopylov, D.A. Andreev,P.Sh. Chomakhidze

Kardiologiya i serdechno-sosudistaya khirurgiyano. 1 (2023): 56-56

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The role of left ventricle global longitudinal srain in prediction of chemotherapy — induced cardiotoxicity in breast cancer patients treated by low and moderate cumulative doses of anthracyclines

V. D. Levina, M. G. Poltavskaya,П. Ш. Чомахидзе, L. V. Bolotina, Т. И. Дешкина,Andrey Meshcheryakov, A. G. Komarova, Zubeida A. Kuli-Zade, А. Г. Комарова, D. S. Valiulina, A. N. Gerasimov

Medicinskij alfavitpp.19-26, (2023)

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Assessment and modification of cardiovascular risk in non-cardiac surgery. Clinical guidelines 2023

А. N. Sumin, D. V. Duplyakov, F. I. Belyalov, А.Е. Баутин, А. В. Безденежных, С. В. Гарькина, М. Л. Гордеев, Д. А. Затейщиков,Olga Irtyuga, E. V. Korok, T. Yu. Kulagina, Е. А. Медведева,

Russian Journal of Cardiologyno. 8 (2023): 5555-5555

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Assessment of left ventricular systolic function using a single-channel ECG monitor with photoplethysmography based on machine learning models