Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning-Reference-Cited by-同舟云学术

Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning

Author:

Samad Manar D¹,Wehner Gregory J²,Arbabshirani Mohammad R¹,Jing Linyuan¹,Powell Andrew J³,Geva Tal³,Haggerty Christopher M¹,Fornwalt Brandon K¹⁴

Affiliation:

1. Department of Imaging Science and Innovation, Center for Health Research, Geisinger Clinic, 100 North Academy Avenue, Danville, 17822-4400 PA, USA

2. Department of Biomedical Engineering, University of Kentucky, 522 Robotics and Manufacturing Building, Lexington, 40506-0108 KY, USA

3. Department of Cardiology, Boston Children's Hospital, 300 Longwood Ave, Boston, 02115 MA, USA

4. Department of Radiology, Geisinger, 100 North Academy Ave, Danville, 17822 PA, USA

Funder

National Institutes of Health

NIH

Director’s Early Independence Award

National Center for Research Resources

National Center for Advancing Translational Sciences

American Heart Association Great Rivers Affiliate

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging,General Medicine

Link

Reference37 articles.

1. Tetralogy of Fallot;Apitz;Lancet,2009

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