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Cedars-Sinai Biomedical Imaging Research Institute Profile
Cedars-Sinai Biomedical Imaging Research Institute

@csmcbiri

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The BIRI mission is to improve the diagnosis, prevention, and treatment of diseases by developing and translating novel medical imaging technologies

Los Angeles, CA
Joined January 2017
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@BJR_Radiology
BIR Journals
2 years
Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems https://t.co/akRrUpxq41 #Radiology #COVID19 #ChestRad #CT @damini_dey @Piotr_JSlomka
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@CedarsSinai
Cedars-Sinai
2 years
Cedars-Sinai is proud to be recognized on U.S. News & World Report’s “Best Hospitals” Honor Roll for 8 years in a row. Join us in thanking our extraordinary staff and physicians, who strive every day to improve healthcare in the U.S. and around the world.
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@BJR_Radiology
BIR Journals
2 years
Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems https://t.co/akRrUpwSet #Radiology #COVID19 #ChestRad #CT @damini_dey @Piotr_JSlomka
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@BrunoLimaMDPhD
Bruno Lima
2 years
Dr Damini Dey (@damini_dey) from @CedarsSinaiMed presenting newer data AI technologies using Deep Learning and Convoluted Neural Networks for coronary plaque analysis. Big takeaway: morphological predictors + plaque quantification improves prognostication. #YesCCT #SCCT2023
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@CedarsSinai
Cedars-Sinai
2 years
In a study published in JAMA Neurology, Marcel Maya, MD, and colleagues found that minimally invasive MRI technologies are just as accurate in detecting cerebrospinal fluid (CSF) leaks, as the standard test, a CT scan. Click below to learn more. ⬇️
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cedars-sinai.org
Dr. Marcel Maya on the talismans that remind him to go outside.
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
New insights into the world of infant development: our brains at 3 mo might set the stage for how we engage socially at 6 mo. A collaboration between BIRI's @Gao_Cedars and the @BeckmanInst highlights the dynamic nature of infant-mother interaction. https://t.co/1F3re1HmXX
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@BJR_Radiology
BIR Journals
2 years
Artificial Intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems https://t.co/JYMrI0kBNx #Radiology #ArtificialIntelligence #COVID19 #ChestRad @damini_dey @Piotr_JSlomka
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
Artificial intelligence in cardiovascular imaging: enhancing image analysis and risk stratification https://t.co/BxC9KN0fPZ
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@bncs_imaging
BNCS_imaging
2 years
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
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@imagingmedsci
imagingmedsci
3 years
New paper published- Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging - PubMed
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pubmed.ncbi.nlm.nih.gov
Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone.
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
New research from @damini_dey and collaborators: In severe aortic stenosis, bicuspid valves have more fibrosis than tricuspid valves, esp. in women. These sex-specific differences may influence early detection, severity grading, and targeted treatment https://t.co/TDwYG19VjB
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
Ever wondered how babies recover from stress? A recent study from the @Gao_Cedars lab and the @BeckmanInst links infant brain connectivity patterns to stress recovery, highlighting the critical role of early brain development in social-emotional function https://t.co/sIEuBjTZ7n
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@RafalWolny
Rafał Wolny
2 years
Pleased to share our research from @nikardiologii on the CT-derived PCAT in SCAD published in @Heart_BMJ. Thanks to @damini_dey for great support. Anyone interested who doesn't have full text access - please DM me. @escardio @PTKardio @HeartSCCT #yescct
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heart.bmj.com
Objective Inflammatory activity is one of the potential mechanisms of spontaneous coronary artery dissection (SCAD). Recently, the pericoronary adipose tissue attenuation (PCAT) derived from CT...
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
Artificial Intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems https://t.co/42ceGkWgBC
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@ctcapapers1
ctca_papers
2 years
Computed tomography-based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment https://t.co/qCbTHPAHu9
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@csmcbiri
Cedars-Sinai Biomedical Imaging Research Institute
2 years
An important consensus statement, co-authored by BIRI's @damini_dey!
@NatRevCardiol
Nature Reviews Cardiology
2 years
Check out our new Consensus Statement by @ProfDewey and the Quantitative Cardiovascular Imaging Study Group on the optimal use of imaging modalities to detect and assess coronary artery stenosis and atherosclerosis | https://t.co/WcKzwvE3UU
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@LondonCardiacCT
LondonCardiacCT
2 years
Cardiac Computed Tomography for Quantification of Myocardial Extracellular Volume Fraction: A Systematic Review and Meta-Analysis | JACC: Cardiovascular Imaging
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jacc.org
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