OpenAlex Citation Counts

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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:

Central apnea detection in premature infants using machine learning
Gabriele Varisco, Zheng Peng, Deedee Kommers, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107155-107155
Open Access | Times Cited: 14

Showing 14 citing articles:

Applications of Artificial Intelligence in Neonatology
Roberto Chioma, Annamaria Sbordone, Maria Letizia Patti, et al.
Applied Sciences (2023) Vol. 13, Iss. 5, pp. 3211-3211
Open Access | Times Cited: 14

Detecting central apneas using multichannel signals in premature infants
Gabriele Varisco, Zheng Peng, Deedee Kommers, et al.
Physiological Measurement (2024) Vol. 45, Iss. 2, pp. 025009-025009
Open Access | Times Cited: 2

Apnea of Prematurity as Manifestation of Immature Control of Breathing: A Mini-Review
Simone Foti Randazzese, Fabio Toscano, F.L. Motta, et al.
Current Respiratory Medicine Reviews (2024) Vol. 21, Iss. 1, pp. 20-28
Closed Access | Times Cited: 1

Current Applications of Artificial Intelligence in the Neonatal Intensive Care Unit
Dimitrios Rallis, Maria Baltogianni, Konstantina Kapetaniou, et al.
BioMedInformatics (2024) Vol. 4, Iss. 2, pp. 1225-1248
Open Access | Times Cited: 1

Current Applications of Artificial Intelligence in the Neonatal Intensive Care Unit
Dimitrios Rallis, Maria Baltogianni, Konstantina Kapetaniou, et al.
(2024)
Open Access

Explainable Machine Learning for Central Apnea Detection in Premature Infants
Gabriele Varisco, Zheng Peng, Peter Andriessen, et al.
2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) (2024), pp. 1-6
Closed Access

Reimagining apnea monitoring in the neonatal ICU
Emily Jeanne, Ruben Alvaro, Wissam Shalish
Current Opinion in Pediatrics (2024) Vol. 37, Iss. 2, pp. 173-181
Closed Access

Exploring Computational Techniques in Pre-processing Neonatal Physiological Signals for Detecting Adverse Outcomes: A Scoping Review (Preprint)
Jessica Sharmin Rahman, Aida Brankovic, Mark Tracy, et al.
Interactive Journal of Medical Research (2024) Vol. 13, pp. e46946-e46946
Open Access

Machine Learning Classification of Pediatric Health Status Based on Cardiorespiratory Signals with Causal and Information Domain Features Applied—An Exploratory Study
Maciej Rosoł, Jakub S. Gąsior, Kacper Korzeniewski, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 23, pp. 7353-7353
Open Access

Artificial intelligence in respiratory care
Manjush Karthika, Jithin K Sreedharan, Madhuragauri Shevade, et al.
Frontiers in Digital Health (2024) Vol. 6
Open Access

Predicting CPAP failure after less invasive surfactant administration (LISA) in preterm infants by machine learning model on vital parameter data: a pilot study
R M J S Kloonen, Gabriele Varisco, Ellen de Kort, et al.
Physiological Measurement (2023) Vol. 44, Iss. 11, pp. 115005-115005
Open Access | Times Cited: 1

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