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:

Outcome Prediction of Postanoxic Coma: A Comparison of Automated Electroencephalography Analysis Methods
Stanley Pham, Hanneke M. Keijzer, Barry J. Ruijter, et al.
Neurocritical Care (2022) Vol. 37, Iss. S2, pp. 248-258
Open Access | Times Cited: 14

Showing 14 citing articles:

AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges
Yohei Okada, Mayli Mertens, Nan Liu, et al.
Resuscitation Plus (2023) Vol. 15, pp. 100435-100435
Open Access | Times Cited: 24
Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury
Zade Akras, Jin Jing, M. Brandon Westover, et al.
Neurotherapeutics (2025), pp. e00524-e00524
Open Access | Times Cited: 1
High density EEG and deep learning improves outcome prediction on the first day of coma after cardiac arrest
Andria Pelentritou, Lyssia Gruaz, Manuela Iten, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Artificial Intelligence in Resuscitation: A Scoping Review
Drieda Zaçe, Federico Semeraro, Sebastian Schnaubelt, et al.
Resuscitation Plus (2025), pp. 100973-100973
Open Access
The effect of artifact rejection on the performance of a convolutional neural network based algorithm for binary EEG data classification
Maritta N. van Stigt, Claudi Ruiz Camps, Jonathan M. Coutinho, et al.
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 105032-105032
Open Access | Times Cited: 9
Prediction of Survival After Pediatric Cardiac Arrest Using Quantitative EEG and Machine Learning Techniques
Maayke Hunfeld, Murielle Verboom, Sabine Josemans, et al.
Neurology (2024) Vol. 103, Iss. 12
Closed Access | Times Cited: 2
Deep learning for EEG-based prognostication after cardiac arrest: from current research to future clinical applications
Frédéric Zubler, Athina Tzovara
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 6
Postresuscitation management
Wilhelm Behringer, Markus B. Skrifvars, Fabio Silvio Taccone
Current Opinion in Critical Care (2023) Vol. 29, Iss. 6, pp. 640-647
Closed Access | Times Cited: 3
Electroencephalogram-based machine learning models to predict neurologic outcome after cardiac arrest: A systematic review
Chao‐Chen Chen, Shavonne L. Massey, Matthew P. Kirschen, et al.
Resuscitation (2023) Vol. 194, pp. 110049-110049
Open Access | Times Cited: 3
Analysis of EEG Signals for Predicting Neurological Recovery in Post-Cardiac Arrest Comatose Patients
Shria Guntunur, Shreya Varma, Shubangi Saxena, et al.
(2024), pp. 64-67
Closed Access
Prediction of Neurological Recovery After Cardiac Arrest Using Deep Learning
Swapnil Makwana, Vijay Sai, S Sethu Madhav, et al.
(2024), pp. 1-9
Closed Access
Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest
Peifeng Ni, Sheng Zhang, Wei Hu, et al.
Resuscitation Plus (2024) Vol. 20, pp. 100829-100829
Closed Access
EEG correlates of the tactile perception of patients in a vegetative state and coma: a step towards AI-based classification of unconscious states
Galina Portnova, Ivan V. Skorokhodov, В. В. Подлепич
The European Physical Journal Special Topics (2024)
Closed Access
Algoritmos genéticos e aprendizado profundo baseado em redes neurais recorrentes do tipo LSTM para auxílio ao diagnóstico médico
Sergio Baldo Júnior
(2023)
Open Access
Page 1

Scroll to top