On the feasibility of tilt test outcome early prediction using ECG and pressure parameters

Autor: García-Alberola A, Rojo-Álvarez JL, Caamaño AJ, Gimeno-Blanes FJ, Flores-Yepes JA

Publikováno v: EURASIP Journal on Advances in Signal Processing, Vol 2011, Iss 1, p 33 (2011)

Abstract The tilt test is a valuable clinical tool for vasovagal syncope (VVS) diagnostic, and its early prediction from simple ECG and blood pressure-based parameters has widely been studied in the literature. However, no practical system is current

Externí odkaz: https://doaj.org/article/f5f92569f96c40b2a6cf2397968fb424

Fetal Heart Rate Analysis for Automatic Detection of Perinatal Hypoxia Using Normalized Compression Distance and Machine Learning.

Autor: Barquero-Pérez Ó; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Santiago-Mozos R; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Lillo-Castellano JM; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., García-Viruete B; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Goya-Esteban R; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Caamaño AJ; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Rojo-Álvarez JL; Department of Signal Theory and Communications, University Rey Juan Carlos Fuenlabrada, Spain., Martín-Caballero C; Department of Obstetrics and Gynaecology, Hospital Universitario Fundación de Alcorcón Madrid, Spain.

Publikováno v: Frontiers in physiology [Front Physiol] 2017 Feb 28; Vol. 8, pp. 113. Date of Electronic Publication: 2017 Feb 28 (Print Publication: 2017).

Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review.

Autor: Salcedo-Sanz, Sancho¹ (AUTHOR), Pérez-Aracil, Jorge¹ (AUTHOR) jorge.perezaracil@uah.es, Ascenso, Guido² (AUTHOR), Del Ser, Javier³ (AUTHOR), Casillas-Pérez, David⁴ (AUTHOR), Kadow, Christopher⁵ (AUTHOR), Fister, Dušan¹ (AUTHOR), Barriopedro, David⁶ (AUTHOR), García-Herrera, Ricardo^6,7 (AUTHOR), Giuliani, Matteo² (AUTHOR), Castelletti, Andrea² (AUTHOR)

Publikováno v: Theoretical & Applied Climatology. Jan2024, Vol. 155 Issue 1, p1-44. 44p.

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A framework for data anomaly detection based on iterative optimization in IoT systems.

Autor: Wang, Zhongmin^1,2,3 (AUTHOR), Wei, Zhihao¹ (AUTHOR) zhwei@stu.xupt.edu.cn, Gao, Cong^1,2,3 (AUTHOR), Chen, Yanping^1,2,3 (AUTHOR), Wang, Fengwei⁴ (AUTHOR)

Publikováno v: Computing. Nov2023, Vol. 105 Issue 11, p2337-2362. 26p.