Detalhe da pesquisa
1.
An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk.
J Electrocardiol
; 76: 61-65, 2023.
Artigo
Inglês
| MEDLINE | ID: mdl-36436476
2.
Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related Stroke.
Circulation
; 143(13): 1287-1298, 2021 03 30.
Artigo
Inglês
| MEDLINE | ID: mdl-33588584
3.
PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger.
Am J Hum Genet
; 102(4): 592-608, 2018 04 05.
Artigo
Inglês
| MEDLINE | ID: mdl-29606303
4.
Routinely reported ejection fraction and mortality in clinical practice: where does the nadir of risk lie?
Eur Heart J
; 41(12): 1249-1257, 2020 03 21.
Artigo
Inglês
| MEDLINE | ID: mdl-31386109
5.
Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants.
Circulation
; 140(1): 42-54, 2019 07 02.
Artigo
Inglês
| MEDLINE | ID: mdl-31216868
6.
A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes.
Genet Med
; 22(1): 102-111, 2020 01.
Artigo
Inglês
| MEDLINE | ID: mdl-31383942
7.
A genome-wide association study of polycystic ovary syndrome identified from electronic health records.
Am J Obstet Gynecol
; 223(4): 559.e1-559.e21, 2020 10.
Artigo
Inglês
| MEDLINE | ID: mdl-32289280
8.
ALG9 Mutation Carriers Develop Kidney and Liver Cysts.
J Am Soc Nephrol
; 30(11): 2091-2102, 2019 11.
Artigo
Inglês
| MEDLINE | ID: mdl-31395617
9.
Electronic health record phenotype in subjects with genetic variants associated with arrhythmogenic right ventricular cardiomyopathy: a study of 30,716 subjects with exome sequencing.
Genet Med
; 19(11): 1245-1252, 2017 11.
Artigo
Inglês
| MEDLINE | ID: mdl-28471438
10.
Association of Rare and Common Variation in the Lipoprotein Lipase Gene With Coronary Artery Disease.
JAMA
; 317(9): 937-946, 2017 03 07.
Artigo
Inglês
| MEDLINE | ID: mdl-28267856
11.
Impact of a Population Genomic Screening Program on Health Behaviors Related to Familial Hypercholesterolemia Risk Reduction.
Circ Genom Precis Med
; 15(5): e003549, 2022 10.
Artigo
Inglês
| MEDLINE | ID: mdl-35862023
12.
Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation.
Circ Genom Precis Med
; 14(5): e003355, 2021 10.
Artigo
Inglês
| MEDLINE | ID: mdl-34463125
13.
Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality.
Nat Biomed Eng
; 5(6): 546-554, 2021 06.
Artigo
Inglês
| MEDLINE | ID: mdl-33558735
14.
Healthcare Utilization and Costs after Receiving a Positive BRCA1/2 Result from a Genomic Screening Program.
J Pers Med
; 10(1)2020 Feb 03.
Artigo
Inglês
| MEDLINE | ID: mdl-32028596
15.
Electronic health record analysis identifies kidney disease as the leading risk factor for hospitalization in confirmed COVID-19 patients.
PLoS One
; 15(11): e0242182, 2020.
Artigo
Inglês
| MEDLINE | ID: mdl-33180868
16.
Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network.
Nat Med
; 26(6): 886-891, 2020 06.
Artigo
Inglês
| MEDLINE | ID: mdl-32393799
17.
A Machine Learning Approach to Management of Heart Failure Populations.
JACC Heart Fail
; 8(7): 578-587, 2020 07.
Artigo
Inglês
| MEDLINE | ID: mdl-32387064
18.
GSTM1 Copy Number Is Not Associated With Risk of Kidney Failure in a Large Cohort.
Front Genet
; 10: 765, 2019.
Artigo
Inglês
| MEDLINE | ID: mdl-31555322
19.
Prevalence and Electronic Health Record-Based Phenotype of Loss-of-Function Genetic Variants in Arrhythmogenic Right Ventricular Cardiomyopathy-Associated Genes.
Circ Genom Precis Med
; 12(11): e002579, 2019 11.
Artigo
Inglês
| MEDLINE | ID: mdl-31638835
20.
Author Correction: Rare variants in drug target genes contributing to complex diseases, phenome-wide.
Sci Rep
; 8(1): 15911, 2018 Oct 23.
Artigo
Inglês
| MEDLINE | ID: mdl-30353015