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Medical Informatics and the Internet in Medicine Volume 27, 2002 - Issue 1
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Research Article

Use of an artificial neural network to differentiate between ECGs with IRBBB patterns of atrial septal defect and healthy subjects

Shu Yang Department of Medical Information & Medical Records, Nagoya University Hospital, 65, Tsurumai-cho, Showa-ku, Nagoya 466-8560, Japan
,
Kazunobu Yamauchi Department of Medical Information & Medical Records, Nagoya University Hospital, 65, Tsurumai-cho, Showa-ku, Nagoya 466-8560, Japan
,
Makoto Nonokawa Department of Medical Information & Medical Records, Nagoya University Hospital, 65, Tsurumai-cho, Showa-ku, Nagoya 466-8560, Japan
&
Mitsuru Ikeda Department of Medical Information & Medical Records, Nagoya University Hospital, 65, Tsurumai-cho, Showa-ku, Nagoya 466-8560, Japan
Pages 49-58 | Published online: 12 Jul 2009

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Damin Huang, Kazunobu Yamauchi, Yasuya Inden, Jun Yang, Zheng Jiang, Hiromasa Ida, Kimiko Katsuyama, Kai Wang, Ken Kato & Hiroki Kato. (2005) Use of an artificial neural network to localize accessory pathways of Wolff–Parkinson–White syndrome with12-lead electrocardiogram. Medical Informatics and the Internet in Medicine 30:4, pages 277-286.
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Articles from other publishers (7)

Ivar R. de Vries, Judith O. E. H. van Laar, Marieke B. van der Hout‐van der Jagt, Sally‐Ann B. Clur & Rik Vullings. (2023) Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease. Acta Obstetricia et Gynecologica Scandinavica 102:11, pages 1511-1520.
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. (2021) Artificial Intelligence in Patients with Congenital Heart Disease: Where Do We Stand?. EMJ Cardiology, pages 70-81.
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Zahra Hoodbhoy, Uswa Jiwani, Saima Sattar, Rehana Salam, Babar Hasan & Jai K. Das. (2021) Diagnostic Accuracy of Machine Learning Models to Identify Congenital Heart Disease: A Meta-Analysis. Frontiers in Artificial Intelligence 4.
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Marinka D. Oudkerk Poo, Dirkjan Kauw, Hidde Bleijendaal, Barbara J.M. Mulder, Yigal Pinto, Berto J. Bouma & Michiel M. Winter. (2020) Artificial Intelligence in Patients with Congenital Heart Disease: Where Do We Stand?. EMJ Cardiology, pages 70-81.
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Shinichi Goto & Shinya Goto. (2019) Application of Neural Networks to 12-Lead Electrocardiography　― Current Status and Future Directions ―. Circulation Reports 1:11, pages 481-486.
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Ikuo Hashimoto, Kazuhiro Watanabe & Fukiko Ichida. (2015) Right to Left Ventricular Diameter Ratio ?0.42 is the Warning Flag for Suspecting Atrial Septal Defect in Preschool Children: Age- and Body Surface Area-Related Reference Values Determined by M-Mode Echocardiography. Pediatric Cardiology 37:4, pages 704-713.
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Ofer Schiller, E. Anne Greene, Jeffrey P. Moak, Marcin Gierdalski & Charles I. Berul. (2013) The Poor Performance of RSR? Pattern on Electrocardiogram Lead V1 for Detection of?Secundum Atrial Septal Defects in Children. The Journal of Pediatrics 162:2, pages 308-312.
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