Joanna X. Liang - Concepedia

Author

Joanna X. Liang

Cedars-Sinai Medical Center

Also Known As

Joanna X. Liang, Joanna Liang, Joanna X Liang, Joanna X. Liang, Ramyashree Tummala

Publications

1.7K

Citations

H-Index

Concepts

All Affiliations

Cedars-Sinai Medical Center Yale University Heart Imaging Technologies (United States)University of Calgary University of Ottawa

About

Joanna X. Liang is an author at Cedars-Sinai Medical Center specializing in cardiology, cardiovascular imaging, and public health.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Public Health	10	10	531
2	Medicine	6	6	335
3	Engineering	4	4	244
4	Health Sciences	4	4	182
5	Biomedical Engineering	2	2	140

Joanna X. Liang

Publications

1.6K

Citations

H-Index

Page 1

	Year	Citations
Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study Julián Betancur, Lien-Hsin Hu, Frédéric Commandeur, Journal of Nuclear Medicine	2018	150
Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT) Piotr J. Slomka, Julián Betancur, Joanna X. Liang, Journal of Nuclear Cardiology Refine SpectEngineeringMedical ImagingCardiovascular DiseaseFast Myocardial Perfusion	2018	109
Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease Yuka Otaki, Ananya Singh, Paul Kavanagh, JACC. Cardiovascular imaging Artificial IntelligenceClinical InnovationHealth SciencesIntelligent DiagnosticsMedical Expert System	2021	107
Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry Lien-Hsin Hu, Julián Betancur, Tali Sharir, European Heart Journal - Cardiovascular Imaging	2019	97
5-Year Prognostic Value of Quantitative Versus Visual MPI in Subtle Perfusion Defects Yuka Otaki, Julián Betancur, Tali Sharir, JACC. Cardiovascular imaging Subtle Perfusion DefectsHeart FailureCardiovascular Disease5-Year Prognostic ValueDiagnosis	2019	92
Impact of train/test sample regimen on performance estimate stability of machine learning in cardiovascular imaging Vikash Kumar Singh, Michael Pencina, Andrew J. Einstein, Scientific Reports	2021	92
Early-life sugar consumption has long-term negative effects on memory function in male rats Emily E. Noble, Ted M. Hsu, Joanna X. Liang, Nutritional Neuroscience	2017	74
Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events Konrad Pieszko, Aakash Shanbhag, Aditya Killekar, JACC. Cardiovascular imaging Computed TomographyEngineeringMachine LearningMedical ImagingCardiovascular Disease	2022	69
Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT Lien-Hsin Hu, Robert J.H. Miller, Tali Sharir, European Heart Journal - Cardiovascular Imaging	2020	63
Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events Robert J.H. Miller, Konrad Pieszko, Aakash Shanbhag, Journal of Nuclear Medicine	2022	56

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