Artificial neural network retrained to detect myocardial ischemia using a Japanese multicenter database.

Journal: Annals of nuclear medicine

Published Date: Jun 1, 2018

Abstract

PURPOSE: An artificial neural network (ANN) has been applied to detect myocardial perfusion defects and ischemia. The present study compares the diagnostic accuracy of a more recent ANN version (1.1) with the initial version 1.0.

Authors

Kenichi Nakajima

Department of Nuclear Medicine, Kanazawa University Hospital.
Koichi Okuda
Satoru Watanabe

Department of Nuclear Medicine, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, 920-8641, Japan.
Shinro Matsuo
Seigo Kinuya
Karin Toth

EXINI Diagnostics, Lund, Sweden.
Lars Edenbrandt

Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Keywords

Aged Area Under Curve Artificial Intelligence Cardiac Surgical Procedures Coronary Angiography Databases as Topic Endovascular Procedures Female Heart Humans Image Interpretation, Computer-Assisted Japan Male Myocardial Ischemia Myocardial Perfusion Imaging Neural Networks, Computer Organotechnetium Compounds Quality Improvement Radiopharmaceuticals ROC Curve Tomography, Emission-Computed, Single-Photon

External Resources

View on PubMed Access via DOI PubMed (29516390)

Artificial neural network retrained to detect myocardial ischemia using a Japanese multicenter database.

Abstract

Authors

Keywords

External Resources

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