| Deep learning analysis of upright-supine high-efficiency SPECT myocardial perfusion imaging for prediction of obstructive coronary artery disease: a multicenter study J Betancur, LH Hu, F Commandeur, T Sharir, AJ Einstein, MB Fish, ... Journal of Nuclear Medicine 60 (5), 664-670, 2019 | 131 | 2019 |
| Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT) PJ Slomka, J Betancur, JX Liang, Y Otaki, LH Hu, T Sharir, S Dorbala, ... Journal of Nuclear Cardiology 27 (3), 1010-1021, 2020 | 84 | 2020 |
| Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry LH Hu, J Betancur, T Sharir, AJ Einstein, S Bokhari, MB Fish, TD Ruddy, ... European Heart Journal-Cardiovascular Imaging 21 (5), 549-559, 2020 | 80 | 2020 |
| 5-year prognostic value of quantitative versus visual MPI in subtle perfusion defects: results from REFINE SPECT Y Otaki, J Betancur, T Sharir, LH Hu, H Gransar, JX Liang, PN Azadani, ... Cardiovascular Imaging 13 (3), 774-785, 2020 | 78 | 2020 |
| Solid-state detector SPECT myocardial perfusion imaging PJ Slomka, RJH Miller, LH Hu, G Germano, DS Berman Journal of Nuclear Medicine 60 (9), 1194-1204, 2019 | 67 | 2019 |
| SPECT myocardial blood flow quantitation toward clinical use: a comparative study with 13N-Ammonia PET myocardial blood flow quantitation B Hsu, LH Hu, BH Yang, LC Chen, YK Chen, CH Ting, GU Hung, ... European journal of nuclear medicine and molecular imaging 44, 117-128, 2017 | 62 | 2017 |
| Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT LH Hu, RJH Miller, T Sharir, F Commandeur, R Rios, AJ Einstein, MB Fish, ... European Heart Journal-Cardiovascular Imaging 22 (6), 705-714, 2021 | 46 | 2021 |
| Impact of early revascularization on major adverse cardiovascular events in relation to automatically quantified ischemia PN Azadani, RJH Miller, T Sharir, MA Diniz, LH Hu, Y Otaki, H Gransar, ... Cardiovascular Imaging 14 (3), 644-653, 2021 | 33 | 2021 |
| Determining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry R Rios, RJH Miller, LH Hu, Y Otaki, A Singh, M Diniz, T Sharir, AJ Einstein, ... Cardiovascular research 118 (9), 2152-2164, 2022 | 32 | 2022 |
| Myocardial ischemic burden and differences in prognosis among patients with and without diabetes: results from the multicenter international REFINE SPECT registry D Han, A Rozanski, H Gransar, T Sharir, AJ Einstein, MB Fish, TD Ruddy, ... Diabetes care 43 (2), 453-459, 2020 | 26 | 2020 |
| Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT E Eisenberg, RJH Miller, LH Hu, R Rios, J Betancur, P Azadani, D Han, ... Journal of Nuclear Cardiology 29 (5), 2295-2307, 2022 | 25 | 2022 |
| Transient ischaemic dilation and post-stress wall motion abnormality increase risk in patients with less than moderate ischaemia: analysis of the REFINE SPECT registry RJH Miller, LH Hu, H Gransar, J Betancur, E Eisenberg, Y Otaki, T Sharir, ... European Heart Journal-Cardiovascular Imaging 21 (5), 567-575, 2020 | 25 | 2020 |
| Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: a report from REFINE SPECT registry LH Hu, T Sharir, RJH Miller, AJ Einstein, MB Fish, TD Ruddy, S Dorbala, ... Journal of Nuclear Cardiology 27 (4), 1180-1189, 2020 | 17 | 2020 |
| Prognostic value of phase analysis for predicting adverse cardiac events beyond conventional single-photon emission computed tomography variables: Results from the REFINE SPECT … K Kuronuma, RJH Miller, Y Otaki, SD Van Kriekinge, MA Diniz, T Sharir, ... Circulation: Cardiovascular Imaging 14 (7), e012386, 2021 | 15 | 2021 |
| Hyperprolactinemia-related 131I uptake in nonlactating breasts LH Hu, SJ Wang, RS Liu Clinical nuclear medicine 37 (3), e57-e58, 2012 | 11 | 2012 |
| Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images RJH Miller, A Singh, Y Otaki, BK Tamarappoo, P Kavanagh, T Parekh, ... European journal of nuclear medicine and molecular imaging 50 (2), 387-397, 2023 | 9 | 2023 |
| Diagnostic accuracy of deep learning for myocardial perfusion imaging in men and women with a high-efficiency parallel-hole-collimated cadmium-zinc-telluride camera … Y Otaki, B Tamarappoo, A Singh, T Sharir, LH Hu, H Gransar, A Einstein, ... Journal of Nuclear Medicine 61 (supplement 1), 92-92, 2020 | 9 | 2020 |
| Simplified quantification of 13N-ammonia PET myocardial blood flow: A comparative study with the standard compartment model to facilitate clinical use CY Chang, GU Hung, B Hsu, BH Yang, CW Chang, LH Hu, WS Huang, ... Journal of Nuclear Cardiology 27, 819-828, 2020 | 5 | 2020 |
| Waders sign on bone scan: A manifestation of portal hypertension YK Chu, LH Hu Clinical Nuclear Medicine 37 (4), 385-386, 2012 | 5 | 2012 |
| Differences in prognostic value of myocardial perfusion single-photon emission computed tomography using high-efficiency solid-state detector between men and women in a large … BK Tamarappoo, Y Otaki, T Sharir, LH Hu, H Gransar, AJ Einstein, ... Circulation: Cardiovascular Imaging 15 (6), e012741, 2022 | 4 | 2022 |
Piotr SlomkaProfessor of Medicine and Cardiology, Artificial Intelligence in Medicine, Cedars-SinaiVerified email at cshs.org
