Literature DB >> 32628923

The Rise of Open-Sourced Machine Learning in Small and Imbalanced Datasets: Predicting In-Stent Restenosis.

Robert Avram1, Jeffrey E Olgin2, Geoffrey H Tison3.   

Abstract

Year:  2020        PMID: 32628923     DOI: 10.1016/j.cjca.2020.02.002

Source DB:  PubMed          Journal:  Can J Cardiol        ISSN: 0828-282X            Impact factor:   5.223


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  2 in total

1.  Simulation-Driven Machine Learning for Predicting Stent Expansion in Calcified Coronary Artery.

Authors:  Pengfei Dong; Guochang Ye; Mehmet Kaya; Linxia Gu
Journal:  Appl Sci (Basel)       Date:  2020-08-22       Impact factor: 2.838

Review 2.  Implementing Machine Learning in Interventional Cardiology: The Benefits Are Worth the Trouble.

Authors:  Walid Ben Ali; Ahmad Pesaranghader; Robert Avram; Pavel Overtchouk; Nils Perrin; Stéphane Laffite; Raymond Cartier; Reda Ibrahim; Thomas Modine; Julie G Hussin
Journal:  Front Cardiovasc Med       Date:  2021-12-08
  2 in total

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