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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:

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier
Franco van Wyk, Anahita Khojandi, Akram Mohammed, et al.
International Journal of Medical Informatics (2018) Vol. 122, pp. 55-62
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
Lucas M. Fleuren, Thomas Klausch, Charlotte Zwager, et al.
Intensive Care Medicine (2020) Vol. 46, Iss. 3, pp. 383-400
Open Access | Times Cited: 484
Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review
Michael Moor, Bastian Rieck, Max Horn, et al.
Frontiers in Medicine (2021) Vol. 8
Open Access | Times Cited: 115
Clinical applications of artificial intelligence in sepsis: A narrative review
Michiel Schinkel, Ketan Paranjape, Rishi Panday, et al.
Computers in Biology and Medicine (2019) Vol. 115, pp. 103488-103488
Open Access | Times Cited: 102
Machine Learning-Based Early Prediction of Sepsis Using Electronic Health Records: A Systematic Review
Khandaker Reajul Islam, Johayra Prithula, Jaya Kumar, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 17, pp. 5658-5658
Open Access | Times Cited: 23
Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission
Shayantan Banerjee, Akram Mohammed, Hector R. Wong, et al.
Frontiers in Immunology (2021) Vol. 12
Open Access | Times Cited: 54
SSP: Early prediction of sepsis using fully connected LSTM-CNN model
Alireza Rafiei, Alireza Rezaee, Farshid Hajati, et al.
Computers in Biology and Medicine (2020) Vol. 128, pp. 104110-104110
Closed Access | Times Cited: 52
Early Detection of Sepsis With Machine Learning Techniques: A Brief Clinical Perspective
Daniele Roberto Giacobbe, Alessio Signori, Filippo Del Puente, et al.
Frontiers in Medicine (2021) Vol. 8
Open Access | Times Cited: 48
Admission vital signs as predictors of COVID-19 mortality: a retrospective cross-sectional study
Ahmed Sameer Ikram, S Pillay
BMC Emergency Medicine (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 33
Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study
Franco van Wyk, Anahita Khojandi, Rishikesan Kamaleswaran
IEEE Journal of Biomedical and Health Informatics (2019) Vol. 23, Iss. 3, pp. 978-986
Closed Access | Times Cited: 43
Machine learning predicts mortality in septic patients using only routinely available ABG variables: a multi-centre evaluation
Bernhard Wernly, Behrooz Mamandipoor, Philipp Heinrich Baldia, et al.
International Journal of Medical Informatics (2020) Vol. 145, pp. 104312-104312
Open Access | Times Cited: 40
The Framing of machine learning risk prediction models illustrated by evaluation of sepsis in general wards
Simon Meyer Lauritsen, Bo Thiesson, Marianne Johansson Jørgensen, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 40
Evaluating machine learning models for sepsis prediction: A systematic review of methodologies
Hongfei Deng, Mingwei Sun, Yu Wang, et al.
iScience (2021) Vol. 25, Iss. 1, pp. 103651-103651
Open Access | Times Cited: 33
A methodological systematic review of validation and performance of sepsis real-time prediction models
Zichen Wang, Wen Wang, Che Sun, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
Clinical Decision-Support Systems for Detection of Systemic Inflammatory Response Syndrome, Sepsis, and Septic Shock in Critically Ill Patients: A Systematic Review
Antje Wulff, Sara Montag, Michael Marschollek, et al.
Methods of Information in Medicine (2019) Vol. 58, Iss. S 02, pp. e43-e57
Open Access | Times Cited: 42
A narrative review of heart rate and variability in sepsis
Benjamin Wee, Jan Hau Lee, Yee Hui Mok, et al.
Annals of Translational Medicine (2020) Vol. 8, Iss. 12, pp. 768-768
Open Access | Times Cited: 38
Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults
Akram Mohammed, Franco van Wyk, Lokesh Chinthala, et al.
Shock (2020) Vol. 56, Iss. 1, pp. 58-64
Open Access | Times Cited: 37
Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review
Nehal Hassan, Robert Slight, Daniel Weiand, et al.
International Journal of Medical Informatics (2021) Vol. 150, pp. 104457-104457
Closed Access | Times Cited: 30
Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients
Akram Mohammed, Yan Cui, Valeria R. Mas, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 33
Digital microbiology
Adrian Egli, Jacques Schrenzel, Gilbert Greub
Clinical Microbiology and Infection (2020) Vol. 26, Iss. 10, pp. 1324-1331
Open Access | Times Cited: 31
Machine Learning Models for Early Prediction of Sepsis on Large Healthcare Datasets
Javier Enrique Camacho-Cogollo, Isis Bonet, Bladimir Gil, et al.
Electronics (2022) Vol. 11, Iss. 9, pp. 1507-1507
Open Access | Times Cited: 18
A Machine Learning–Enabled Partially Observable Markov Decision Process Framework for Early Sepsis Prediction
Zeyu Liu, Anahita Khojandi, Xueping Li, et al.
INFORMS journal on computing (2022) Vol. 34, Iss. 4, pp. 2039-2057
Closed Access | Times Cited: 16
Dynamic Prediction of Patient Outcomes in the Intensive Care Unit: A Scoping Review of the State-of-the-Art
Linda Lapp, Marc Roper, Kimberley Kavanagh, et al.
Journal of Intensive Care Medicine (2023) Vol. 38, Iss. 7, pp. 575-591
Open Access | Times Cited: 8
A review on the significance of body temperature interpretation for early infectious disease diagnosis
Nurul Izzati Darul Zaman, Yuan Wen Hau, Ming Chern Leong, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. 12, pp. 15449-15494
Closed Access | Times Cited: 7
Dissecting contributions of individual systemic inflammatory response syndrome criteria from a prospective algorithm to the prediction and diagnosis of sepsis in a polytrauma cohort
Roman Schefzik, Bianka Hahn, Verena Schneider‐Lindner
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 7
Corticosteroid sensitivity detection in sepsis patients using a personalized data mining approach: A clinical investigation
Rahma Hellali, Zaineb Chelly Dagdia, Ahmed Ktaish, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 245, pp. 108017-108017
Open Access | Times Cited: 2
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