Kenichi Nakajima, Takashi Kudo, Tomoaki Nakata, Keisuke Kiso, Tokuo Kasai, Yasuyo Taniguchi, Shinro Matsuo, Mitsuru Momose, Masayasu Nakagawa, Masayoshi Sarai, Satoshi Hida, Hirokazu Tanaka, Kunihiko Yokoyama, Koichi Okuda, Lars Edenbrandt
PURPOSE: Artificial neural networks (ANN) might help to diagnose coronary artery disease. This study aimed to determine whether the diagnostic accuracy of an ANN-based diagnostic system and conventional quantitation are comparable. METHODS: The ANN was trained to classify potentially abnormal areas as true or false based on the nuclear cardiology expert interpretation of 1001 gated stress/rest 99m Tc-MIBI images at 12 hospitals. The diagnostic accuracy of the ANN was compared with 364 expert interpretations that served as the gold standard of abnormality for the validation study...
December 2017: European Journal of Nuclear Medicine and Molecular Imaging