Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type-Reference-Cited by-同舟云学术

Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type

Published:2021-10-05 Issue:6 Volume:8 Page:4626-4634
ISSN:2055-5822
Container-title:ESC Heart Failure
language:en
Short-container-title:ESC Heart Failure

Author:

Javaid Awad I.¹^ORCID,Monlezun Dominique J.²³^ORCID,Iliescu Gloria²,Tran Phi⁴,Filipescu Alexandru⁵,Palaskas Nicolas²,Lopez‐Mattei Juan²,Hassan Saamir²,Kim Peter²,Madjid Mohammad⁴,Cilingiroglu Mehmet²,Charitakis Konstantinos⁴,Marmagkiolis Konstantinos²,Iliescu Cezar²^ORCID,Koutroumpakis Efstratios⁴

Affiliation:

1. Division of Cardiovascular Medicine Kirk Kerkorian School of Medicine at the University of Nevada Las Vegas 1701 W Charleston Blvd Las Vegas NV USA

2. Department of Cardiology The University of Texas M.D. Anderson Cancer Center Houston TX USA

3. Center for Artificial Intelligence and Health Equities Global System Analytics & Structures New Orleans LA USA

4. Division of Cardiology The University of Texas Health Sciences Center at Houston Houston TX USA

5. Department of Obstetrics and Gynecology “Elias” Emergency University Hospital Bucharest Romania

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ehf2.13647

Reference35 articles.

1. Clinical Features and Outcomes of Patients With Malignancy and Takotsubo Syndrome: Observations From the International Takotsubo Registry

2. Outcomes of Takotsubo cardiomyopathy in hospitalized cancer patients

3. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group

4. Comparison of Propensity Score Methods and Covariate Adjustment

5. Intravenous Tissue Plasminogen Activator for Wake-Up Stroke: A Propensity Score-Matched Analysis

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