Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram
John M. O’Toole, Geraldine B. Boylan, Sampsa Vanhatalo, et al.
Clinical Neurophysiology (2016) Vol. 127, Iss. 8, pp. 2910-2918
Closed Access | Times Cited: 60

Showing 26-50 of 60 citing articles:

Brain age as an estimator of neurodevelopmental outcome: A deep learning approach for neonatal cot-side monitoring
Amir H. Ansari, Kirubin Pillay, Luke Baxter, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Lost in Transition: A Systematic Review of Neonatal Electroencephalography in the Delivery Room—Are We Forgetting an Important Biomarker for Newborn Brain Health?
Daragh Finn, Eugene Dempsey, Geraldine B. Boylan
Frontiers in Pediatrics (2017) Vol. 5
Open Access | Times Cited: 11
Monitoring Effective Connectivity in the Preterm Brain: A Graph Approach to Study Maturation
Mario Lavanga, Ofelie De Wel, Alexander Caicedo, et al.
Complexity (2017) Vol. 2017, pp. 1-13
Open Access | Times Cited: 11
Background suppression of electrical activity is a potential biomarker of subsequent brain injury in a rat model of neonatal hypoxia-ischemia
Andrew Zayachkivsky, Mark J. Lehmkuhle, Jeffrey J. Ekstrand, et al.
Journal of Neurophysiology (2022) Vol. 128, Iss. 1, pp. 118-130
Open Access | Times Cited: 6
Sleep state organisation of moderate to late preterm infants in the neonatal unit
Mary Anne Ryan, Sean Mathieson, Vicki Livingstone, et al.
Pediatric Research (2022) Vol. 93, Iss. 3, pp. 595-603
Open Access | Times Cited: 6
Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG
Xiaowan Wang, Anne Bik, Eline R. de Groot, et al.
Clinical Neurophysiology (2022) Vol. 146, pp. 55-64
Open Access | Times Cited: 6
Multiscale entropy analysis of combined EEG-fNIRS measurement in preterm neonates
Lorenzo Semeia, Mina Nourhashemi, Mahdi Mahmoudzadeh, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 3
It’s All About the Brain—Neuromonitoring During Newborn Transition
Eugene Dempsey, Elisabeth M. W. Kooi, Geraldine B. Boylan
Seminars in Pediatric Neurology (2018) Vol. 28, pp. 48-59
Open Access | Times Cited: 9
Results of quantitative EEG analysis are associated with autism spectrum disorder and development abnormalities in infants with tuberous sclerosis complex
Mario Lavanga, Jessie De Ridder, Katarzyna Kotulska, et al.
Biomedical Signal Processing and Control (2021) Vol. 68, pp. 102658-102658
Closed Access | Times Cited: 8
The degree of prematurity affects functional brain activity in preterm born children at school-age: An EEG study
Charlotte van ’t Westende, Cacha Peeters‐Scholte, Lisette Jansen, et al.
Early Human Development (2020) Vol. 148, pp. 105096-105096
Open Access | Times Cited: 6
Sensory event-related potential morphology predicts age in premature infants
Coen S. Zandvoort, Marianne van der Vaart, Shellie Robinson, et al.
Clinical Neurophysiology (2023) Vol. 157, pp. 61-72
Open Access | Times Cited: 2
Comparison of conventional, amplitude-integrated and geodesic sensor net EEG used in premature neonates: a systematic review
Tainã Maria Alves de Sousa, Vinicius Siessere Gugelmin, Geraldo Magela Fernandes, et al.
Arquivos de Neuro-Psiquiatria (2019) Vol. 77, Iss. 4, pp. 260-267
Open Access | Times Cited: 5
Deep learning for estimation of functional brain maturation from EEG of premature neonates
Laura P Gschwandtner, M. Hartmann, Lisa Oberdorfer, et al.
(2020), pp. 104-107
Closed Access | Times Cited: 5
Random Convolution Kernels with Multi-Scale Decomposition for Preterm EEG Inter-burst Detection
Christopher Lundy, John M. O’Toole
2021 29th European Signal Processing Conference (EUSIPCO) (2021), pp. 1182-1186
Open Access | Times Cited: 5
Quantitative assessment of neurodevelopmental maturation: a comprehensive systematic literature review of artificial intelligence-based brain age prediction in pediatric populations
Eric Dragendorf, Eva Bültmann, Dominik Wolff
Frontiers in Neuroinformatics (2024) Vol. 18
Open Access
Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG
Sumit A. Raurale, Saif Nalband, Geraldine B. Boylan, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 3
Machine learning without a feature set for detecting bursts in the EEG of preterm infants
John M. Toole, Geraldine B. Boylan
(2019), pp. 5799-5802
Open Access | Times Cited: 3
Inter-site generalizability of EEG based age prediction algorithms in the preterm infant
Nathan J. Stevenson, Tone Nordvik, Cathrine Nygaard Espeland, et al.
Physiological Measurement (2023) Vol. 44, Iss. 7, pp. 07NT01-07NT01
Closed Access | Times Cited: 1
Oscillatory characteristics in the brain activity of the newborns and their correlation with different gestational ages
Maksim О. Zhuravlev, Alesia Akimova, Olga S. Panina, et al.
Izvestiya VUZ Applied Nonlinear Dynamics (2023)
Open Access | Times Cited: 1
Examining time–frequency mechanisms of full-fledged deep sleep development in newborns of different gestational age in the first days of their postnatal development
Anton R. Kiselev, Oxana M. Drapkina, Mikhail Novikov, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 2
Machine learning without a feature set for detecting bursts in the EEG of preterm infants
John M. O’Toole, Geraldine B. Boylan
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 2
Grading the severity of hypoxic-ischemic encephalopathy in newborn EEG using a convolutional neural network
Sumit A. Raurale, Geraldine B. Boylan, Gordon Lightbody, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 2
A high performing EEG approach for the automated scoring of the sleep stages of neonates
Stavros I. Dimitriadis
Clinical Neurophysiology (2017) Vol. 128, Iss. 6, pp. 1039-1040
Open Access | Times Cited: 1
Identifying neurophysiological features associated with anesthetic state in newborn mice and humans
Mattia Chini, Sabine Gretenkord, Johanna K. Kostka, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2018)
Open Access | Times Cited: 1
Mathematical Analysis of EEG Concordance in Preterm Twin Infants
Rhodri O. Lloyd, John M. O’Toole, Vicki Livingstone, et al.
Journal of Clinical Neurophysiology (2019) Vol. 38, Iss. 1, pp. 62-68
Closed Access | Times Cited: 1

Scroll to top