Application of machine learning algorithms for predicting internal carotid artery stenosis and comparing their value to duplex Doppler ultrasonography criteria-Reference-Cited by-同舟云学术

Application of machine learning algorithms for predicting internal carotid artery stenosis and comparing their value to duplex Doppler ultrasonography criteria

Published:2021-09-24 Issue: Volume: Page:
ISSN:1309-9833
Container-title:Pamukkale Medical Journal
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Author:

ÇELTİKÇİ Pınar,ERASLAN Önder,ATICI Mehmet,CONKBAYIR Işık,ERGUN Onur,DURMAZ Hasanali,ÇELTİKÇİ Emrah

Publisher

Pamukkale University

Subject

General Medicine

Reference22 articles.

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2. 2. European Carotid Trialists' Collaborative Group. Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST). Lancet 1998;351:1379–1387.

3. 3. Endarterectomy for asymptomatic carotid artery stenosis. Executive Committee for the Asymptomatic Carotid Atherosclerosis Study. JAMA 1995;273:1421–1428.

4. 4. Arning C, Widder B, von Reutern GM, et al. Revision of DEGUM ultrasound criteria for grading internal carotid artery stenoses and transfer to NASCET measurement. Ultraschall Med 2010;31:251–257. https://doi.org/10.1055/s-0029-1245336

5. 5. Hathout GM, Fink JR, El-Saden SM, Grant EG. Sonographic NASCET index: a new doppler parameter for assessment of internal carotid artery stenosis. AJNR Am J Neuroradiol 2005;26:68–75.

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