Machine learning techniques versus complexity theory in the cerebral haemodynamics of traumatic brain injury patients-Reference-Cited by-同舟云学术

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Machine learning techniques versus complexity theory in the cerebral haemodynamics of traumatic brain injury patients

Published:2021-11-02 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Latin American Conference on Computational Intelligence (LA-CCI)
language:
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Author:

Lobos Vasquez Maria Fernanda¹,Alcivar-Cevallos Roberth²,Panerai Ronney B.³,Chacon Max¹

Affiliation:

1. Universidad de Santiago de Chile,Departamento de Ingeniería Informática,Santiago,Chile

2. Universidad Técnica de Manabí,Facultad de Ciencias Informáticas,Ecuador

3. University of Leicester,Cardiovascular Sciences Department,Leicester,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9769800/9769778/09769819.pdf?arnumber=9769819

Reference22 articles.

1. Distinguishing Noise from Chaos

2. Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review

3. New Support Vector Algorithms

4. Fractal Variability Versus Pathologic Periodicity: Complexity Loss and Stereotypy in Disease

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