Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc.: Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics

Silvia Schöntaler; Christa Nöhammer; Monika Olischar; Angelika Berger; Gregor Kasprian; Georg Langs; Klemens Vierlinger; Nicholas  Nicoletti; Rakesh  Lavu; Wei  Liu; Sreenivas  Karnati; Subhash  Puthuraya; Helen L  Turner; James P  Boardman; Nicola J  Robertson; Ana Laguna  Pradas; Bernhard  Schwaberger; Gerhard Pichler; Mohamed  El-Dib; Seth  Goldstein; John  Sunwoo; Sarah Schlatterer

doi:10.3233/npm-249004

Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics

, Silvia Schöntaler
, Christa Nöhammer
, Monika Olischar
, Angelika Berger
, Gregor Kasprian
, Georg Langs
, Klemens Vierlinger
, Nicholas Nicoletti
, Rakesh Lavu
, Wei Liu
, Sreenivas Karnati
, Subhash Puthuraya
, Helen L Turner
, James P Boardman
, Nicola J Robertson
, Ana Laguna Pradas
, Bernhard Schwaberger
, Gerhard Pichler
, Mohamed El-Dib

Seth Goldstein, John Sunwoo, Sarah Schlatterer

Molecular Diagnostics

Cleveland Clinic Foundation
Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Medical University of Vienna
Medical University of Vienna
Department of Biomedical Imaging and Image-Guided Therapy, Division of Neuro- and Musculosceletal Radiology, Medical University of Vienna
Cleveland Clinic Children’s Hospital
Centre for Clinical Brain Sciences, The University of Edinburgh
University of Barcelona
Division of Neonatology, Department of Pediatrics and Adolescent Medicine, Medical University of Graz
Division of Newborn Medicine, Department of Pediatrics, Brigham and Women’s Hospital, Harvard Medical School
Ann & Robert H. Lurie Children’s Hospital of Chicago
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Department of Neurology, George Washington University School of Medicine and Health Sciences

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

Abstract

Preterm neonates with intraventricular hemorrhage (IVH) are at risk for posthemorrhagic ventricular dilatation (PHVD). In recent years targeted proteomics has developed into a powerful protein quantiﬁ cation tool in biomedical research, systems biology, and clinical applications. This study aims to inform therapeutic decision-making and parental counseling using proteomics in this high-risk group.

Originalsprache	Englisch
Aufsatznummer	1
Seiten (von - bis)	S393-S394
Seitenumfang	2
Fachzeitschrift	Journal of Neonatal-Perinatal Medicine
Issue	17
DOIs	https://doi.org/10.3233/npm-249004
Publikationsstatus	Veröffentlicht - 5 Aug. 2024

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 3 – Gute Gesundheit und Wohlergehen

Research Field

Molecular Diagnostics

Schlagwörter

Machine learning
pediatrics
Biomarker discovery

Web of Science subject categories (JCR Impact Factors)

Medicine, Research & Experimental

Zugriff auf Dokument

10.3233/npm-249004

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, Schöntaler, S., Nöhammer, C., Olischar, M., Berger, A., Kasprian, G., Langs, G., Vierlinger, K., Nicoletti, N., Lavu, R., Liu, W., Karnati, S., Puthuraya, S., Turner, H. L., Boardman, J. P., Robertson, N. J., Pradas, A. L., Schwaberger, B., Pichler, G., ... Schlatterer, S. (2024). Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics. Journal of Neonatal-Perinatal Medicine, (17), S393-S394. Artikel 1. https://doi.org/10.3233/npm-249004

Schöntaler, Silvia ; Nöhammer, Christa et al. / Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics. in: Journal of Neonatal-Perinatal Medicine. 2024 ; Nr. 17. S. S393-S394.

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abstract = "Preterm neonates with intraventricular hemorrhage (IVH) are at risk for posthemorrhagic ventricular dilatation (PHVD). In recent years targeted proteomics has developed into a powerful protein quantiﬁ cation tool in biomedical research, systems biology, and clinical applications. This study aims to inform therapeutic decision-making and parental counseling using proteomics in this high-risk group.",

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Schöntaler, S, Nöhammer, C, Olischar, M, Berger, A, Kasprian, G, Langs, G, Vierlinger, K, Nicoletti, N, Lavu, R, Liu, W, Karnati, S, Puthuraya, S, Turner, HL, Boardman, JP, Robertson, NJ, Pradas, AL, Schwaberger, B, Pichler, G, El-Dib, M, Goldstein, S & Sunwoo, J & Schlatterer, S 2024, 'Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics', Journal of Neonatal-Perinatal Medicine, Nr. 17, 1, S. S393-S394. https://doi.org/10.3233/npm-249004

Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics. /; Schöntaler, Silvia; Nöhammer, Christa et al.
in: Journal of Neonatal-Perinatal Medicine, Nr. 17, 1, 05.08.2024, S. S393-S394.

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

TY - JOUR

T1 - Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc.

T2 - Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics

AU - Acun, Ceyda

AU - Aly, Hany

AU - Bauerstätter, Priska

AU - Goeral, Katharina

AU - Schöntaler, Silvia

AU - Nöhammer, Christa

AU - Olischar, Monika

AU - Berger, Angelika

AU - Kasprian, Gregor

AU - Langs, Georg

AU - Vierlinger, Klemens

AU - Nicoletti, Nicholas

AU - Lavu, Rakesh

AU - Liu, Wei

AU - Karnati, Sreenivas

AU - Puthuraya, Subhash

AU - Turner, Helen L

AU - Boardman, James P

AU - Robertson, Nicola J

AU - Pradas, Ana Laguna

AU - Schwaberger, Bernhard

AU - Pichler, Gerhard

AU - El-Dib, Mohamed

AU - Goldstein, Seth

AU - Sunwoo, John

AU - Schlatterer, Sarah

PY - 2024/8/5

Y1 - 2024/8/5

N2 - Preterm neonates with intraventricular hemorrhage (IVH) are at risk for posthemorrhagic ventricular dilatation (PHVD). In recent years targeted proteomics has developed into a powerful protein quantiﬁ cation tool in biomedical research, systems biology, and clinical applications. This study aims to inform therapeutic decision-making and parental counseling using proteomics in this high-risk group.

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KW - Machine learning

KW - pediatrics

KW - Biomarker discovery

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Schöntaler S, Nöhammer C, Olischar M, Berger A, Kasprian G et al. Proceedings of the 15th International Newborn Brain Conference: Other forms of brain monitoring, such as NIRS, fMRI, biochemical, etc. Machine learning predicts outcomes in preterm neonates with intraventricular hemorrhage using targeted proteomics. Journal of Neonatal-Perinatal Medicine. 2024 Aug. 5;(17):S393-S394. 1. doi: 10.3233/npm-249004