Complex Systems in Biomedicine

Quarteroni, Alfio; Formaggia, Luca; Veneziani, Alessandro

doi:10.1007/88-470-0396-2

Cited by 36 publications

(1 citation statement)

References 27 publications

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“…The main feature of the physiological systems -their complexity "hidden" in the biomedical signals. The processing of these signals in terms of complex systems provides the possibilities to perceive the system components and dynamic interrelationships [6], [7]. The breakthrough in the complex system theory broadened the area of its application -from the molecular to the body levels.…”

Section: Introductionmentioning

confidence: 99%

Method for Predicting of Acute Hypotensive Episodes

Petkus¹,

Vainoras

Berškienė

et al. 2016

ElAEE

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Hypotension is type of secondary insult and it is related to poor outcome. The ability to predict adverse hypotensive events, where a patient's arterial blood pressure drops to abnormally low levels, would be of major benefit to the fields of primary and secondary health care. The aim of the paper is to present the novel method for predicting of acute hypotensive episodes, based on ECG analysis by the complex system theory approach. 45 patients (in four neurointensive care facilities throughout Europe) data were selected for the analysis. 11 patients had EUSIG-defined hypotensive events. The method includes determining of time varying biomarkers corresponding to plurality of physiological processes in patient's organism as a non-linear dynamic complex system and generating an acute hypotension prediction classifier. The calculations of biomarkers are based on complex system approach and algebraic matrix analysis of ECG parameters. The classifier is based on the comparison of biomarkers behaviour in 3D images. It is demonstrated that the presented method allows us to predict arterial hypotension events 40-50 minutes ahead with a sensitivity of 81 %, specificity 94 %. This result was obtained from prospective real-time data collection in a live clinical intensive care environment.

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Section: Introductionmentioning

confidence: 99%

Method for Predicting of Acute Hypotensive Episodes

Petkus¹,

Vainoras

Berškienė

et al. 2016

ElAEE

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Philosophical Aspects of Neuropsychiatry

Tretter¹

2010

Systems Biology in Psychiatric Research

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Systems Biology in Psychiatric Research: From Complex Data Sets Over Wiring Diagrams to Computer Simulations

Tretter

Gebicke‐Haerter

2011

Methods in Molecular Biology

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The classification of psychiatric disorders has always been a problem in clinical settings. The present debate about the major systems in clinical practice, DSM-IV and ICD-10, has resulted in attempts to improve and replace those schemes by some that include more endophenotypic and molecular features. However, these disorders not only require more precise diagnostic tools, but also have to be viewed more extensively in their dynamic behaviors, which require more precise data sets related to their origins and developments. This enormous challenge in brain research has to be approached on different levels of the biological system by new methods, including improvements in electroencephalography, brain imaging, and molecular biology. All these methods entail accumulations of large data sets that become more and more difficult to interpret. In particular, on the molecular level, there is an apparent need to use highly sophisticated computer programs to tackle these problems. Evidently, only interdisciplinary work among mathematicians, physicists, biologists, and clinicians can further improve our understanding of complex diseases of the brain.

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Complex Systems in Biomedicine

Abstract: The picture on the cover shows an integration of a synapsis (bottom right), the computational domain for a pulmonary artery bifurcation (top right), the human heart (top left), and the wall shear stress in a pulmonary artery (bottom left).

Cited by 36 publications

References 27 publications

Method for Predicting of Acute Hypotensive Episodes

Method for Predicting of Acute Hypotensive Episodes

Philosophical Aspects of Neuropsychiatry

Systems Biology in Psychiatric Research: From Complex Data Sets Over Wiring Diagrams to Computer Simulations

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