Development and Validation of Artificial Intelligence–based Method for Diagnosis of Mitral Regurgitation from Chest Radiographs-Reference-Cited by-同舟云学术

Development and Validation of Artificial Intelligence–based Method for Diagnosis of Mitral Regurgitation from Chest Radiographs

Published:2022-03-01 Issue:2 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Ueda Daiju¹^ORCID,Ehara Shoichi¹^ORCID,Yamamoto Akira¹^ORCID,Iwata Shinichi¹^ORCID,Abo Koji¹,Walston Shannon L.¹^ORCID,Matsumoto Toshimasa¹^ORCID,Shimazaki Akitoshi¹^ORCID,Yoshiyama Minoru¹,Miki Yukio¹^ORCID

Affiliation:

1. From the Department of Diagnostic and Interventional Radiology (D.U., A.Y., S.L.W., T.M., A.S., Y.M.) and Department of Cardiovascular Medicine (S.E., S.I., M.Y.), Graduate School of Medicine, Osaka City University, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan; and the Central Clinical Laboratory, Osaka City University Hospital, Osaka, Japan (K.A.).

Funder

Japan Society for the Promotion of Science

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210221

Reference18 articles.

1. A prospective survey of patients with valvular heart disease in Europe: The Euro Heart Survey on Valvular Heart Disease

2. Burden of valvular heart diseases: a population-based study

3. 2017 AHA/ACC Focused Update of the 2014 AHA/ACC Guideline for the Management of Patients With Valvular Heart Disease