Last Posted: Jan 02, 2020
- Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: Evaluation of a machine learning risk prediction algorithm.
Hill Nathan R et al. Journal of medical economics 2019 Dec 1 - Association of Race With Disease Expression and Clinical Outcomes Among Patients With Hypertrophic Cardiomyopathy.
Eberly Lauren A, et al. JAMA cardiology 2019 12 0. - Diagnosing With a Camera From a Distance—Proceed Cautiously and Responsibly
MP Turakhia, JAMA Cardiology, November 2019 - Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation
MV Perez et al, NEJM, November 13, 2019 - Predicting atrial fibrillation in primary care using machine learning.
Hill Nathan R et al. PloS one 2019 14(11) e0224582 - Broad Genetic Testing in a Clinical Setting Uncovers a High Prevalence of Titin Loss-of-Function Variants in Very Early-Onset Atrial Fibrillation.
Goodyer William R et al. Circulation. Genomic and precision medicine 2019 Oct - CYP2D6 Genotype-guided Metoprolol Therapy in Cardiac Surgery Patients: Rationale and Design of the Pharmacogenetic-guided Metoprolol Management for Postoperative Atrial Fibrillation in Cardiac Surgery (PREEMPTIVE) Pilot Study.
Dunham Wills C et al. Journal of cardiothoracic and vascular anesthesia 2019 Sep - Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases.
Zhu Ye et al. Genetics in medicine : official journal of the American College of Medical Genetics 2019 Oct - Atrial Fibrillation Genetics Update: Toward Clinical Implementation.
Kalstø Silje Madeleine et al. Frontiers in cardiovascular medicine 2019 6127 - Leveraging Human Genetics to Estimate Clinical Risk Reductions Achievable by Inhibiting Factor XI.
Georgi Benjamin et al. Stroke 2019 Sep STROKEAHA119026545
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