Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

Paul Bogdan; Plamen Ch Ivanov; Sergio Pequito

doi:10.3389/fphys.2022.917001

Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

Paul Bogdan^*, Plamen Ch Ivanov, Sergio Pequito^*

^*Corresponding author for this work

Team Sergio Pequito

Research output: Contribution to journal › Editorial › Scientific › peer-review

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Abstract

Editorial on the Research Topic - Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

Original language	English
Article number	917001
Number of pages	3
Journal	Frontiers in Physiology
Volume	13
DOIs	https://doi.org/10.3389/fphys.2022.917001
Publication status	Published - 2022

Keywords

artificial Inteligence-AI
fractional-order dynamic models
multifractal networks
neuro-inspired artificial intelligence
physiology

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10.3389/fphys.2022.917001

fphys-13-917001Final published version, 563 KBLicence: CC BY

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title = "Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence",

abstract = "Editorial on the Research Topic - Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence",

keywords = "artificial Inteligence-AI, fractional-order dynamic models, multifractal networks, neuro-inspired artificial intelligence, physiology",

author = "Paul Bogdan and Ivanov, {Plamen Ch} and Sergio Pequito",

year = "2022",

doi = "10.3389/fphys.2022.917001",

language = "English",

volume = "13",

journal = "Frontiers in Physiology",

issn = "1664-042X",

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Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence. / Bogdan, Paul; Ivanov, Plamen Ch; Pequito, Sergio.
In: Frontiers in Physiology, Vol. 13, 917001, 2022.

Research output: Contribution to journal › Editorial › Scientific › peer-review

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T1 - Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

AU - Bogdan, Paul

AU - Ivanov, Plamen Ch

AU - Pequito, Sergio

PY - 2022

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AB - Editorial on the Research Topic - Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

KW - artificial Inteligence-AI

KW - fractional-order dynamic models

KW - multifractal networks

KW - neuro-inspired artificial intelligence

KW - physiology

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U2 - 10.3389/fphys.2022.917001

DO - 10.3389/fphys.2022.917001

M3 - Editorial

AN - SCOPUS:85130884262

SN - 1664-042X

VL - 13

JO - Frontiers in Physiology

JF - Frontiers in Physiology

M1 - 917001

ER -

Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

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Keywords

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