An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

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An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence

Institution:	1. Department of Cardiology, Boston Children''s Hospital, and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts;2. One Brave Idea, Division of Cardiovascular Medicine, Brigham and Women''s Hospital and Harvard Medical School, Boston, Massachusetts;1. University of Washington School of Medicine, Seattle, Washington;2. Indiana University School of Medicine, Indianapolis, Indiana;1. Department of Biomedical Engineering, Medical College of Wisconsin, and Marquette University, Milwaukee, Wisconsin;2. Division of Pediatric Cardiology, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin;3. Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Herma Heart Institute, Children''s Wisconsin, Milwaukee, Wisconsin;4. Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin;5. Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin;6. Department of Medicine, Division of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin;7. Department of Mathematics and Statistical Sciences, Marquette University, Milwaukee, Wisconsin;1. Labatt Family Heart Center, Department of Pediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada;2. Fetal and Neonatal Cardiology Program, Division of Cardiology, Department of Pediatrics, Stollery Children’s Hospital, Edmonton, Alberta, Canada;3. Department of Obstetrics & Gynecology, University of Alberta, Edmonton, Alberta, Canada;1. Department of Cardiology and the Department of Medicine, Scripps Mercy Hospital, San Diego, California;2. Brown University, Providence, Rhode Island;1. National Heart Centre, Singapore, Singapore;2. Duke-National University of Singapore Medical School, Singapore, Singapore;3. University Medical Centre Groningen, Groningen, The Netherlands;4. CardioVascular Institute and Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts;5. Harvard Medical School, Boston, Massachusetts;1. Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts;2. Cardiovascular Performance Program, Massachusetts General Hospital, Boston, Massachusetts;3. Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts

Abstract:

Keywords:	Artificial intelligence Pediatric cardiology Convolutional neural network View classification Echocardiography A2C"} {"#name":"keyword" "$":{"id":"kwrd0040"} "$$":[{"#name":"text" "_":"Apical two-chamber A3C"} {"#name":"keyword" "$":{"id":"kwrd0050"} "$$":[{"#name":"text" "_":"Apical three-chamber A4C"} {"#name":"keyword" "$":{"id":"kwrd0060"} "$$":[{"#name":"text" "_":"Apical four-chamber A4C MV PW"} {"#name":"keyword" "$":{"id":"kwrd0070"} "$$":[{"#name":"text" "_":"Mitral valve pulsed-wave Doppler tracing AI"} {"#name":"keyword" "$":{"id":"kwrd0080"} "$$":[{"#name":"text" "_":"Artificial intelligence CHD"} {"#name":"keyword" "$":{"id":"kwrd0090"} "$$":[{"#name":"text" "_":"Congenital heart disease CNN"} {"#name":"keyword" "$":{"id":"kwrd0100"} "$$":[{"#name":"text" "_":"Convolutional neural network HLP Transverse"} {"#name":"keyword" "$":{"id":"kwrd0110"} "$$":[{"#name":"text" "_":"High left parasternal transverse branch pulmonary arteries PLAX"} {"#name":"keyword" "$":{"id":"kwrd0120"} "$$":[{"#name":"text" "_":"Parasternal long-axis PLAX AoV"} {"#name":"keyword" "$":{"id":"kwrd0130"} "$$":[{"#name":"text" "_":"Parasternal long-axis aortic valve PSAX PM"} {"#name":"keyword" "$":{"id":"kwrd0140"} "$$":[{"#name":"text" "_":"Parasternal short-axis papillary muscle level SC SAX Sweep"} {"#name":"keyword" "$":{"id":"kwrd0150"} "$$":[{"#name":"text" "_":"Subcostal short-axis sweep
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