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7. Machine Learning Algorithm to Predict Atrial Fibrillation Using Serial 12-Lead ECGs Based on Left Atrial Remodeling. Choi JH; Song SH; Kim H; Kim J; Park H; Jeon J; Hong J; Gwag HB; Lee SH; Lee J; Cho SJ; Park SJ; On YK; Kim JY; Park KM J Am Heart Assoc; 2024 Oct; 13(19):e034154. PubMed ID: 39344663 [TBL] [Abstract][Full Text] [Related]
8. Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis. Han L; Askari M; Altman RB; Schmitt SK; Fan J; Bentley JP; Narayan SM; Turakhia MP Circ Cardiovasc Qual Outcomes; 2019 Oct; 12(10):e005595. PubMed ID: 31610712 [TBL] [Abstract][Full Text] [Related]
9. Refining Prediction of Atrial Fibrillation-Related Stroke Using the P Maheshwari A; Norby FL; Roetker NS; Soliman EZ; Koene RJ; Rooney MR; O'Neal WT; Shah AM; Claggett BL; Solomon SD; Alonso A; Gottesman RF; Heckbert SR; Chen LY Circulation; 2019 Jan; 139(2):180-191. PubMed ID: 30586710 [TBL] [Abstract][Full Text] [Related]
10. Atrial time and voltage dispersion are both needed to predict new-onset atrial fibrillation in ischemic stroke patients. Cortez D; Baturova M; Lindgren A; Carlson J; Shubik YV; Olsson B; Platonov PG BMC Cardiovasc Disord; 2017 Jul; 17(1):200. PubMed ID: 28738786 [TBL] [Abstract][Full Text] [Related]
11. Clinical relevance of assessing QT dynamicity in Holter recordings. Coumel P; Fayn J; Maison-Blanche P; Rubel P J Electrocardiol; 1994; 27 Suppl():62-6. PubMed ID: 7884377 [TBL] [Abstract][Full Text] [Related]
12. [Detection model of atrial fibrillation based on multi-branch and multi-scale convolutional networks]. Zhao S; Liu M; Liu M; Yang X; Xiong P; Zhang J Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2024 Aug; 41(4):700-707. PubMed ID: 39218595 [TBL] [Abstract][Full Text] [Related]
13. Machine Learning-Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes. Tang S; Razeghi O; Kapoor R; Alhusseini MI; Fazal M; Rogers AJ; Rodrigo Bort M; Clopton P; Wang PJ; Rubin DL; Narayan SM; Baykaner T Circ Arrhythm Electrophysiol; 2022 Aug; 15(8):e010850. PubMed ID: 35867397 [TBL] [Abstract][Full Text] [Related]
14. Changes of QT intervals associated with postural change in patients with chronic atrial fibrillation. Malik M; Janota T; Nagayoshi H; Hnatkova K; Camm AJ Pacing Clin Electrophysiol; 1996 Apr; 19(4 Pt 1):490-5. PubMed ID: 8848398 [TBL] [Abstract][Full Text] [Related]
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16. Slower heart rate and altered rate dependence of ventricular repolarization in patients with lone atrial fibrillation. Maury P; Caudron G; Bouisset F; Fourcade J; Duparc A; Mondoly P; Rollin A; Hascoët S; Detis N; Cardin C; Delay M; Lairez O; Roncalli J; Galinier M; Carrié D; Elbaz M; Ferrières J; Fauvel JM; Zimmermann M Arch Cardiovasc Dis; 2013 Jan; 106(1):12-8. PubMed ID: 23374967 [TBL] [Abstract][Full Text] [Related]
17. Prediction of atrial fibrillation in patients with cardiac dysfunctions: P wave signal-averaged ECG and chemoreflexsensitivity in atrial fibrillation. Budeus M; Hennersdorf M; Felix O; Reimert K; Perings C; Wieneke H; Erbel R; Sack S Europace; 2007 Aug; 9(8):601-7. PubMed ID: 17507361 [TBL] [Abstract][Full Text] [Related]
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20. Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal. Ebrahimzadeh E; Kalantari M; Joulani M; Shahraki RS; Fayaz F; Ahmadi F Comput Methods Programs Biomed; 2018 Oct; 165():53-67. PubMed ID: 30337081 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]