Artificial intelligence for automated evaluation of aortic measurements in 2D echocardiography: Feasibility, accuracy, and reproducibility.

Autor: Karužas, Arnas^1,2 arnas.karuzas@lsmu.lt, Balčiūnas, Justinas², Fukson, Mark², Verikas, Dovydas^1,2, Matuliauskas, Dovydas², Platūkis, Tautvydas³, Vaičiulienė, Dovilė³, Jurgaitytė, Julija³, Kupstytė‐Krištaponė, Nora³, Dirsienė, Rūta⁴, Jaruševičius, Gediminas¹, Šakalytė, Gintarė¹, Plisienė, Jurgita⁴, Lesauskaitė, Vaiva¹

Publikováno v: Echocardiography. Nov2022, Vol. 39 Issue 11, p1439-1445. 7p.

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Left atrial deformation parameters for the assessment of hemodynamically significant coronary artery stenosis in patients with intermmediate pretest probability of coronary artery disease

Autor: Rumbinaitė, Eglė, Karužas, Arnas, Sakavičiūtė, Emilija, Jonauskienė, Ieva, Karaliūtė, Rasa, Lapinskas, Tomas, Vaškelytė, Jolanta Justina

Publikováno v: European Heart Journal-Cardiovascular Imaging : Abstracts of EUROECHO 2017 : The Twenty-First Annual Meeting of the European Association of Echocardiography : Lisbon, 6-9 December 2017 / European Association of Cardiovascular Imaging (EACVI). European Society of Cardiology (ESC), Oxford : Oxford University Press, 2017, vol. 18, suppl. 3, p. iii65-iii65, no. P302

Introduction: The role of left ventricle (LV) longitudinal deformation parameters in detecting hemodynamically significant coronary artery disease (CAD) have been shown in previuos studies. However, still little is known about the diagnostic value o

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https://library.lsmuni.lt/LSMU:ELABAPDB25298986&prefLang=en_US

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