Zobrazeno 1 - 10 of 10 pro vyhledávání: '"Cathleen, Huang"'
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Akademický článek
Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography
Autor: Robert J. H. Miller, Aditya Killekar, Aakash Shanbhag, Bryan Bednarski, Anna M. Michalowska, Terrence D. Ruddy, Andrew J. Einstein, David E. Newby, Mark Lemley, Konrad Pieszko, Serge D. Van Kriekinge, Paul B. Kavanagh, Joanna X. Liang, Cathleen Huang, Damini Dey, Daniel S. Berman, Piotr J. Slomka
Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Chest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ven
Externí odkaz: https://doaj.org/article/4c588a8fbc88488b95dfaa67b3daf6af
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2
Akademický článek
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational studyResearch in context
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
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7
Machine Learning to Predict Abnormal Myocardial Perfusion from Pre-test Features
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/
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8
Integration of coronary artery calcium scoring from CT attenuation scans by machine learning improves prediction of adverse cardiovascular events in patients undergoing SPECT/CT myocardial perfusion imaging
Autor: Attila Feher, Konrad Pieszko, Robert Miller, Mark Lemley, Aakash Shanbhag, Cathleen Huang, Leonidas Miras, Yi-Hwa Liu, Albert J. Sinusas, Edward J. Miller, Piotr J. Slomka
Publikováno v: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.
Machine learning (ML) has been previously applied for prognostication in patients undergoing SPECT myocardial perfusion imaging (MPI). We evaluated whether including attenuation CT coronary artery calcification (CAC) scoring improves ML prediction of
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe7b7191a255ac095b5457a588e63138
https://pubmed.ncbi.nlm.nih.gov/36598750
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9
Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology
Autor: Robert J H, Miller, Cathleen, Huang, Joanna X, Liang, Piotr J, Slomka
Publikováno v: Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology. 29(4)
Artificial intelligence (AI) techniques have emerged as a highly efficient approach to accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear cardiology. In nuclear cardiology, there are many clinical, stress, and im
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::b39cb855ea028b123abacdeac0463908
https://pubmed.ncbi.nlm.nih.gov/35508795
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