Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Mathews B Fish"'
Autor:
Robert J.H. Miller, Bryan P. Bednarski, Konrad Pieszko, Jacek Kwiecinski, Michelle C. Williams, Aakash Shanbhag, Joanna X. Liang, Cathleen Huang, Tali Sharir, M. Timothy Hauser, Sharmila Dorbala, Marcelo F. Di Carli, Mathews B. Fish, Terrence D. Ruddy, Timothy M. Bateman, Andrew J. Einstein, Philipp A. Kaufmann, Edward J. Miller, Albert J. Sinusas, Wanda Acampa, Donghee Han, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Publikováno v:
EBioMedicine, Vol 99, Iss , Pp 104930- (2024)
Summary: Background: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal result
Externí odkaz:
https://doaj.org/article/1ebd9b1ba5254425a0a74eefbe0cbb75
Autor:
Konrad Pieszko, Aakash D. Shanbhag, Ananya Singh, M. Timothy Hauser, Robert J. H. Miller, Joanna X. Liang, Manish Motwani, Jacek Kwieciński, 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 Di Carli, Daniel S. Berman, Damini Dey, Piotr J. Slomka
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-11 (2023)
Abstract Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is mo
Externí odkaz:
https://doaj.org/article/75978cd7a5ab4ab0a242e50b065ae7c0
Autor:
Ananya Singh, Robert J.H. Miller, Yuka Otaki, Paul Kavanagh, Michael T. Hauser, Evangelos Tzolos, Jacek Kwiecinski, Serge Van Kriekinge, Chih-Chun Wei, 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 Di Carli, Joanna X. Liang, Cathleen Huang, Donghee Han, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Publikováno v:
JACC: Cardiovascular Imaging. 16:209-220
Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.We developed an explainable deep learning (DL) model (HARD MACE [major adverse cardiac events]-D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ace9148f767bbbfb7fb572451bc9e74b
https://doi.org/10.1016/j.jcmg.2022.07.017
https://doi.org/10.1016/j.jcmg.2022.07.017
Autor:
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
Publikováno v:
Eur J Nucl Med Mol Imaging
PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96b00df91da9216c0f0bcad4613846d9
https://doi.org/10.1007/s00259-022-05972-w
https://doi.org/10.1007/s00259-022-05972-w
Autor:
Mathews B. Fish, Heidi Gransar, Edward J. Miller, Terrence D. Ruddy, Damini Dey, Robert J.H. Miller, Marcelo F. Di Carli, Lien-Hsin Hu, Andrew J. Einstein, Philipp A. Kaufmann, Sharmila Dorbala, Joanna X Liang, Piotr J. Slomka, Albert J. Sinusas, Evangelos Tzolos, Donghee Han, Timothy M. Bateman, Tali Sharir, Daniel S. Berman, Alan Rozanski
Publikováno v:
J Nucl Cardiol
BACKGROUND: Diabetes mellitus (DM) is increasingly prevalent among contemporary populations referred for cardiac stress testing, but its potency as a predictor for major adverse cardiovascular events (MACE) versus other clinical variables is not well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07a6527dd195a4965746c98a14a93b34
https://www.zora.uzh.ch/id/eprint/227952/
https://www.zora.uzh.ch/id/eprint/227952/
Autor:
Donghee Han, Alan Rozanski, Robert J. H. Miller, 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 Di Carli, Joanna X. Liang, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Publikováno v:
J Nucl Cardiol
BACKGROUND: The utility of cardiac stress testing depends on the prevalence of myocardial ischemia within candidate populations. However, a comprehensive assessment of the factors influencing frequency of myocardial ischemia within contemporary popul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13302075c3c06fef224a248cd7baa2e3
https://www.zora.uzh.ch/id/eprint/227949/
https://www.zora.uzh.ch/id/eprint/227949/
Autor:
Timothy M. Bateman, Sabahat Bokhari, Terrence D. Ruddy, Julian Betancur, Daniel S. Berman, Yuka Otaki, Donghee Han, Edward J. Miller, Sharmila Dorbala, Andrew J. Einstein, Joanna X Liang, Piotr J. Slomka, Albert J. Sinusas, Mathews B. Fish, Richard Rios, Lien-Hsin Hu, Tali Sharir, Philipp A. Kaufmann, Damini Dey, Peyman N. Azadani, Robert J.H. Miller, Marcelo F. Di Carli, Balaji Tamarappoo, Evann Eisenberg
Publikováno v:
J Nucl Cardiol
BACKGROUND: Stress-only myocardial perfusion imaging (MPI) markedly reduces radiation dose, scanning time, and cost. We developed an automated clinical algorithm to safely cancel unnecessary rest imaging with high sensitivity for obstructive coronary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ae563a8331baca5d55222dff0c2595c
https://doi.org/10.5167/uzh-208811
https://doi.org/10.5167/uzh-208811
Autor:
Terrence D. Ruddy, Marcio A. Diniz, Edward J. Miller, Robert J.H. Miller, Marcelo F. Di Carli, Damini Dey, Philipp A. Kaufmann, Paul B. Kavanagh, Mathews B. Fish, Tejas Parekh, Ananya Singh, Tali Sharir, Serge D. Van Kriekinge, Sharmila Dorbala, Joanna X Liang, Daniel S. Berman, Albert J. Sinusas, Richard Rios, Lien-Hsin Hu, Timothy M. Bateman, Andrew J. Einstein, Piotr J. Slomka, Yuka Otaki
Publikováno v:
Cardiovascular Research. 118:2152-2164
AIMS Optimal risk stratification with machine learning (ML) from myocardial perfusion imaging (MPI) includes both clinical and imaging data. While most imaging variables can be derived automatically, clinical variables require manual collection, whic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40828a528559a4827f15beaae708e3ea
https://doi.org/10.1093/cvr/cvab236
https://doi.org/10.1093/cvr/cvab236
Publikováno v:
Journal of Nuclear Cardiology. 29:1219-1230
We hypothesized early post-stress left ventricular ejection fraction reserve (EFR) on solid-state-SPECT is associated with major cardiac adverse events (MACE). 151 patients (70 ± 12 years, male 50%) undergoing same-day rest/regadenoson stress 99mTc-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::538fb948467237e3cf241678e63b3852
https://doi.org/10.1007/s12350-020-02420-w
https://doi.org/10.1007/s12350-020-02420-w
Autor:
Robert J. H. Miller, M. Timothy Hauser, 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 Di Carli, Cathleen Huang, Joanna X. Liang, Donghee Han, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Publikováno v:
J Nucl Cardiol
BACKGROUND: Accurately predicting which patients will have abnormal perfusion on MPI based on pre-test clinical information may help physicians make test selection decisions. We developed and validated a machine learning (ML) model for predicting abn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d2f42cd6d791623144b4008c4e05777
https://europepmc.org/articles/PMC9588501/
https://europepmc.org/articles/PMC9588501/