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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:

Vital sign‐based detection of sepsis in neonates using machine learning
Antoine Honoré, David Forsberg, Katja Adolphson, et al.
Acta Paediatrica (2023) Vol. 112, Iss. 4, pp. 686-696
Open Access | Times Cited: 21

Showing 21 citing articles:

Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring
Fang Li, Shengguo Wang, Zhi Gao, et al.
Frontiers in Medicine (2025) Vol. 11
Open Access | Times Cited: 1
Diagnosis and Management of Neonatal Bacterial Sepsis: Current Challenges and Future Perspectives
Domenico Umberto De Rose, Maria Paola Ronchetti, Ludovica Martini, et al.
Tropical Medicine and Infectious Disease (2024) Vol. 9, Iss. 9, pp. 199-199
Open Access | Times Cited: 7
The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping and in silico modeling to identify new therapeutics
Dan Liu, Jordan C. Langston, Balabhaskar Prabhakarpandian, et al.
Frontiers in Cellular and Infection Microbiology (2024) Vol. 13
Open Access | Times Cited: 6
A novel deep learning-based approach for prediction of neonatal respiratory disorders from chest X-ray images
Ayşe Yildirim, Murat Canayaz
Journal of Applied Biomedicine (2023) Vol. 43, Iss. 4, pp. 635-655
Closed Access | Times Cited: 7
Diagnostic performance of machine-learning algorithms for sepsis prediction: An updated meta-analysis
Hongru Zhang, Chen Wang, Ning Yang
Technology and Health Care (2024) Vol. 32, Iss. 6, pp. 4291-4307
Closed Access | Times Cited: 2
Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor
Meicheng Yang, Zheng Peng, Carola van Pul, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 255, pp. 108335-108335
Open Access | Times Cited: 2
Weight a minute: The smaller and more immature, the more predictable the autonomic regulation?
Alexander Stålhammar, Antoine Honoré, Katja Adolphson, et al.
Acta Paediatrica (2023) Vol. 112, Iss. 7, pp. 1443-1452
Open Access | Times Cited: 4
The use of probabilistic graphical models in pediatric sepsis: a feasibility and scoping review
Tuong Minh Nguyen, Kim Leng Poh, Shu‐Ling Chong, et al.
Translational Pediatrics (2023) Vol. 12, Iss. 11, pp. 2074-2089
Open Access | Times Cited: 3
Early Detection of Late Onset Sepsis in Extremely Preterm Infants Using Machine Learning: Towards an Early Warning System
Arno G. Garstman, Cristian Rodrìguez Rivero, Wes Onland
Applied Sciences (2023) Vol. 13, Iss. 16, pp. 9049-9049
Open Access | Times Cited: 2
The Finnegan Score for Neonatal Opioid Withdrawal Revisited With Routine Electronic Data: Retrospective Study
Till Rech, Kerstin Rubarth, Christoph Bührer, et al.
JMIR Pediatrics and Parenting (2023) Vol. 7, pp. e50575-e50575
Open Access | Times Cited: 2
Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment
Sapiah Sakri, Shakila Basheer, Zuhaira Muhammad Zain, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 1, pp. 1157-1185
Open Access
Diagnostic Performance of Machine Learning-based Models in Neonatal Sepsis: A Systematic Review
Deepika Kainth, Satya Prakash, M. Jeeva Sankar
The Pediatric Infectious Disease Journal (2024) Vol. 43, Iss. 9, pp. 889-901
Open Access
Heart rate and oxygen saturation patterns in very low birth weight infants with early onset sepsis and histologic chorioamnionitis
Charlene R. Bultmann, Jiaxang Qiu, Briana M. Belmonte, et al.
Journal of Neonatal-Perinatal Medicine (2024) Vol. 17, Iss. 2, pp. 209-215
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
A systematic literature review of predictive analytics methods for early diagnosis of neonatal sepsis
K. V. K. L. Narasimha Rao, Pradeep Kumar Dadabada, Sanjita Jaipuria
Deleted Journal (2024) Vol. 21, Iss. 1
Open Access
AI Algorithms for Modeling the Risk, Progression, and Treatment of Sepsis, Including Early-Onset Sepsis—A Systematic Review
Karolina Tądel, Andrzej Dudek, Iwona Bil‐Lula
Journal of Clinical Medicine (2024) Vol. 13, Iss. 19, pp. 5959-5959
Open Access
A retrospective evaluation of SwePEWS use in paediatric patients with COVID‐19 and RSV infection
Julia Bodlund, Albin Wimmerdahl, Antoine Honoré, et al.
Acta Paediatrica (2024)
Open Access
Early detection of sepsis using machine learning algorithms
Rasha M. Abd El-Aziz, Alanazi Rayan
Alexandria Engineering Journal (2024) Vol. 111, pp. 47-56
Open Access
The Finnegan score for neonatal opioid withdrawal revisited by routine electronic data: a retrospective study (Preprint)
Till Rech, Kerstin Rubarth, Christoph Bührer, et al.
(2023)
Closed Access | Times Cited: 1
Physiological Signal Analysis Techniques for Preterm Infants in Detecting Adverse Outcomes: A Review (Preprint)
Jessica Sharmin Rahman, Aida Brankovic, Mark Tracy, et al.
(2023)
Open Access
Issue highlights
Anna Käll, Hugo Lagercrantz
Acta Paediatrica (2023) Vol. 112, Iss. 4, pp. 578-579
Open Access
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