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3. Novel Density Poincaré Plot Based Machine Learning Method to Detect Atrial Fibrillation From Premature Atrial/Ventricular Contractions. Bashar SK; Han D; Zieneddin F; Ding E; Fitzgibbons TP; Walkey AJ; McManus DD; Javidi B; Chon KH IEEE Trans Biomed Eng; 2021 Feb; 68(2):448-460. PubMed ID: 32746035 [TBL] [Abstract][Full Text] [Related]
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12. Detection of atrial fibrillation using discrete-state Markov models and Random Forests. Kalidas V; Tamil LS Comput Biol Med; 2019 Oct; 113():103386. PubMed ID: 31446318 [TBL] [Abstract][Full Text] [Related]
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16. Automatic real time detection of atrial fibrillation. Dash S; Chon KH; Lu S; Raeder EA Ann Biomed Eng; 2009 Sep; 37(9):1701-9. PubMed ID: 19533358 [TBL] [Abstract][Full Text] [Related]
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19. Ranking of the most reliable beat morphology and heart rate variability features for the detection of atrial fibrillation in short single-lead ECG. Christov I; Krasteva V; Simova I; Neycheva T; Schmid R Physiol Meas; 2018 Sep; 39(9):094005. PubMed ID: 30102603 [TBL] [Abstract][Full Text] [Related]
20. The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation. Dörr M; Nohturfft V; Brasier N; Bosshard E; Djurdjevic A; Gross S; Raichle CJ; Rhinisperger M; Stöckli R; Eckstein J JACC Clin Electrophysiol; 2019 Feb; 5(2):199-208. PubMed ID: 30784691 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]