Detalhe da pesquisa
1.
Development of novel machine learning model for right ventricular quantification on echocardiography-A multimodality validation study.
Echocardiography
; 37(5): 688-697, 2020 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-32396705
2.
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.
Eur Heart J
; 40(24): 1975-1986, 2019 06 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-30060039
3.
Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.
J Cardiovasc Magn Reson
; 21(1): 1, 2019 01 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-30612574
4.
Using electronic health records for population health sciences: a case study to evaluate the associations between changes in left ventricular ejection fraction and the built environment.
JAMIA Open
; 3(3): 386-394, 2020 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-33215073
5.
Utilizing electronic health data and machine learning for the prediction of 30-day unplanned readmission or all-cause mortality in heart failure.
Cardiovasc Digit Health J
; 1(2): 71-79, 2020.
Artigo
em Inglês
| MEDLINE | ID: mdl-35265878
6.
Clinical and Socioeconomic Predictors of Heart Failure Readmissions: A Review of Contemporary Literature.
Mayo Clin Proc
; 94(7): 1304-1320, 2019 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-31272573
7.
Discharge Processes and 30-Day Readmission Rates of Patients Hospitalized for Heart Failure on General Medicine and Cardiology Services.
Am J Cardiol
; 121(9): 1076-1080, 2018 05 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-29548676
8.
Patterns of scheduled follow-up appointments following hospitalization for heart failure: insights from an urban medical center in the United States.
Clin Interv Aging
; 11: 1325-1332, 2016.
Artigo
em Inglês
| MEDLINE | ID: mdl-27713623
9.
A Novel Deep Learning Approach for Automated Diagnosis of Acute Ischemic Infarction on Computed Tomography.
JACC Cardiovasc Imaging
; 11(11): 1723-1725, 2018 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-29778866