Martine Neckebroek

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A compact fractional-order model for hypnosis in general anesthesia

Marcian Mihai, Isabela Roxana Birs (UGent) , Erwin Hegedus, Dana Copot (UGent) , Robain De Keyser (UGent) , Clara-Mihaela Ionescu (UGent) , Cristina Muresan and Martine Neckebroek (UGent)

(2024) IFAC PAPERSONLINE. 58(12). p.55-60

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A fractional order impedance model for heterogeneous drug distribution in obese patients during general anesthesia

Amani Rayene Ynineb (UGent) , Erhan Yumuk (UGent) , Hamed Farbakhsh (UGent) , Ghada Ben Othman (UGent) , Dana Copot (UGent) , Isabela Roxana Birs (UGent) , Cristina Muresan, Robain De Keyser (UGent) , Samir Ladaci, Clara-Mihaela Ionescu (UGent) , et al.

(2024) IFAC PAPERSONLINE. 58(12). p.61-66

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First-hand design of a fractional order PID for controlling the depth of hypnosis during induction

Marcian Mihai, Isabela Roxana Birs (UGent) , Erwin Hegedus, Dana Copot (UGent) , Martine Neckebroek (UGent) , Robain De Keyser (UGent) , Clara-Mihaela Ionescu (UGent) and Cristina Muresan

(2024) IFAC PAPERSONLINE. 58(7). p.186-191

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PID control of data-driven patient response with fixed ratio co-administration of drugs for depth of hypnosis

Clara-Mihaela Ionescu (UGent) , Hamed Farbakhsh (UGent) , Cristina Muresan, Robain De Keyser (UGent) , Erhan Yumuk (UGent) , Ghada Ben Othman (UGent) , Amani Rayene Ynineb (UGent) , Isabela Roxana Birs (UGent) , Dana Copot (UGent) and Martine Neckebroek (UGent)

(2024) IFAC PAPERSONLINE. 58(7). p.222-227

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Fractional-order modeling of the depth of analgesia as reference model for control purposes

Cristina Muresan, Erwin T. Hegedüs, Marcian D. Mihai, Ghada Ben Othman (UGent) , Isabela Roxana Birs (UGent) , Dana Copot (UGent) , Eva Henrietta Dulf, Robain De Keyser (UGent) , Clara-Mihaela Ionescu (UGent) and Martine Neckebroek (UGent)

(2024) FRACTAL AND FRACTIONAL. 8(9).

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Model extraction from clinical data subject to large uncertainties and poor identifiability

Clara-Mihaela Ionescu (UGent) , Robain De Keyser (UGent) , Dana Copot (UGent) , Erhan Yumuk (UGent) , Amani Rayene Ynineb (UGent) , Ghada Ben Othman (UGent) and Martine Neckebroek (UGent)

(2024) IEEE CONTROL SYSTEMS LETTERS. 8. p.2151-2156

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Selecting optimal Long Short-Term Memory (LSTM) architectures for online estimation of mean arterial pressure (MAP) in patients undergoing general anesthesia

Ghada Ben Othman (UGent) , Dana Copot (UGent) , Erhan Yumuk (UGent) , Martine Neckebroek (UGent) and Clara-Mihaela Ionescu (UGent)

(2024) APPLIED SCIENCES-BASEL. 14(13).

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Data-driven identification and comparison of full multivariable models for propofol-remifentanil induced general anesthesia

Erhan Yumuk (UGent) , Dana Copot (UGent) , Clara-Mihaela Ionescu (UGent) and Martine Neckebroek (UGent)

(2024) JOURNAL OF PROCESS CONTROL. 139.

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Development, validation, and comparison of a novel nociception/anti-nociception monitor against two commercial monitors in general anesthesia

Clara-Mihaela Ionescu (UGent) , Dana Copot (UGent) , Erhan Yumuk (UGent) , Robain De Keyser (UGent) , Cristina Muresan, Isabela Roxana Birs (UGent) , Ghada Ben Othman (UGent) , Hamed Farbakhsh (UGent) , Amani Rayene Ynineb (UGent) and Martine Neckebroek (UGent)

(2024) SENSORS. 24(7).

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Parametric modeling and deep learning for enhancing pain assessment in postanesthesia

Mihaela Ghita (UGent) , Isabela Roxana Birs (UGent) , Dana Copot (UGent) , Cristina Muresan, Martine Neckebroek (UGent) and Clara-Mihaela Ionescu (UGent)

(2023) IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. 70(10). p.2991-3002

Academic Bibliography

Martine Neckebroek

A compact fractional-order model for hypnosis in general anesthesia

A fractional order impedance model for heterogeneous drug distribution in obese patients during general anesthesia

First-hand design of a fractional order PID for controlling the depth of hypnosis during induction

PID control of data-driven patient response with fixed ratio co-administration of drugs for depth of hypnosis

Fractional-order modeling of the depth of analgesia as reference model for control purposes

Model extraction from clinical data subject to large uncertainties and poor identifiability

Selecting optimal Long Short-Term Memory (LSTM) architectures for online estimation of mean arterial pressure (MAP) in patients undergoing general anesthesia

Data-driven identification and comparison of full multivariable models for propofol-remifentanil induced general anesthesia

Development, validation, and comparison of a novel nociception/anti-nociception monitor against two commercial monitors in general anesthesia

Parametric modeling and deep learning for enhancing pain assessment in postanesthesia

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