Last Posted: May 12, 2020
- Big Data and Atrial Fibrillation: Current Understanding and New Opportunities.
Wang Qian-Chen et al. Journal of cardiovascular translational research 2020 May - Detection of Atrial Fibrillation from Single Lead ECG Signal Using Multirate Cosine Filter Bank and Deep Neural Network.
Ghosh S K et al. Journal of medical systems 2020 May 44(6) 114 - Integrating the STOP-BANG score and clinical data to predict cardiovascular events after infarction: A machine learning study.
Calvillo-Argüelles Oscar et al. Chest 2020 Apr - Predicting long-term freedom from atrial fibrillation after catheter ablation by a machine learning algorithm: Validation of the CAAP-AF score.
Furui Koichi et al. Journal of arrhythmia 2020 Apr 36(2) 297-303 - Wolff-Parkinson-White syndrome: De novo variants and evidence for mutational burden in genes associated with atrial fibrillation.
Coban-Akdemir Zeynep H et al. American journal of medical genetics. Part A 2020 Mar - Accuracy of Smartphone Camera Applications for Detecting Atrial Fibrillation- A Systematic Review and Meta-analysis
JW O'SUllivan et al, JAMA Network Open, April 3, 2020 - Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.
Wu Xueyi et al. Hypertension (Dallas, Tex. : 1979) 2020 Mar HYPERTENSIONAHA11913404 - The Genetic Puzzle of Familial Atrial Fibrillation.
Ragab Ahmed A Y et al. Frontiers in cardiovascular medicine 2020 714 - Artificial Intelligence in Medicine: Today and Tomorrow.
Briganti Giovanni et al. Frontiers in medicine 2020 727 - Polygenic Risk Scores in Coronary Artery Disease and Atrial Fibrillation.
Gladding Patrick A et al. Heart, lung & circulation 2019 Dec
.png)
No hay comentarios:
Publicar un comentario