Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images

Miller, R. J. H., Singh, A., Otaki, Y., Tamarappoo, B. K., Kavanagh, P., Parekh, T., Hu, L.-H., Gransar, H., Sharir, T., Einstein, A. J., Fish, M. B., Ruddy, T. D., Kaufmann, P. A., Sinusas, A. J., Miller, E. J., Bateman, T. M., Dorbala, S., Di Carli, M. F., Liang, J. X., … Slomka, P. J. (2022). Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images. European Journal of Nuclear Medicine and Molecular Imaging, 50(2), 387–397. https://doi.org/10.1007/s00259-022-05972-w
Authors:
Robert J H Miller
Ananya Singh
Yuka Otaki
Balaji K Tamarappoo
Paul Kavanagh
Tejas Parekh
Lien-Hsin Hu
Heidi Gransar
Tali Sharir
Andrew J Einstein
Mathews B Fish
Terrence D Ruddy
Philipp A Kaufmann
Albert J Sinusas
Edward J Miller
Timothy M Bateman
Sharmila Dorbala
Marcelo F Di Carli
Joanna X Liang
Damini Dey
Daniel S Berman
Piotr J Slomka
Affiliated Authors:
Andrew J Einstein
Author Keywords:
deep learning
model training
calibration
diagnostic accuracy
sex-specific analysis
Publication Type:
Article
Unique ID:
10.1007/s00259-022-05972-w
PMID:
Publication Date:
Data Source:
PubMed

Record Created: