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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 Machine Learning-Based Prediction of Hospital Mortality in Patients With Postoperative Sepsis
Ren-qi Yao, Xin Jin, Guowei Wang, et al.
Frontiers in Medicine (2020) Vol. 7
Open Access | Times Cited: 58

Showing 26-50 of 58 citing articles:

A nomogram for predicting mortality risk within 30 days in sepsis patients admitted in the emergency department: A retrospective analysis
Bin Wang, Jianping Chen, Xinling Pan, et al.
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0296456-e0296456
Open Access | Times Cited: 2
Machine learning-based prognostic model for 30-day mortality prediction in Sepsis-3
Md. Sohanur Rahman, Khandaker Reajul Islam, Johayra Prithula, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Predicting COVID-19 mortality risk in Toronto, Canada: a comparison of tree-based and regression-based machine learning methods
Cindy Feng, George Kephart, Elizabeth Juarez‐Colunga
BMC Medical Research Methodology (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 14
The prediction power of machine learning on estimating the sepsis mortality in the intensive care unit
Selcuk Mehtap, Oguz Koc, A. Sevtap Selcuk‐Kestel
Informatics in Medicine Unlocked (2022) Vol. 28, pp. 100861-100861
Open Access | Times Cited: 9
Data and model bias in artificial intelligence for healthcare applications in New Zealand
Vithya Yogarajan, Gillian Dobbie, Sharon Leitch, et al.
Frontiers in Computer Science (2022) Vol. 4
Open Access | Times Cited: 9
Predictive value of lymphocyte‐to‐monocyte ratio in critically Ill patients with atrial fibrillation: A propensity score matching analysis
Yue Yu, Suyu Wang, Pei Wang, et al.
Journal of Clinical Laboratory Analysis (2021) Vol. 36, Iss. 2
Open Access | Times Cited: 12
A machine learning-based prediction of hospital mortality in mechanically ventilated ICU patients
Hexin Li, Negin Ashrafi, Chris Kang, et al.
PLoS ONE (2024) Vol. 19, Iss. 9, pp. e0309383-e0309383
Open Access | Times Cited: 1
Sepsis-Associated Coagulopathy Predicts Hospital Mortality in Critically Ill Patients With Postoperative Sepsis
Chao Ren, Yuxuan Li, Demeng Xia, et al.
Frontiers in Medicine (2022) Vol. 9
Open Access | Times Cited: 6
ACEI/ARB Medication During ICU Stay Decrease All-Cause In-hospital Mortality in Critically Ill Patients With Hypertension: A Retrospective Cohort Study Based on Machine Learning
Boshen Yang, Sixuan Xu, Di Wang, et al.
Frontiers in Cardiovascular Medicine (2022) Vol. 8
Open Access | Times Cited: 5
Using Machine Learning Algorithms to predict sepsis and its stages in ICU patients
Nimrah Ghias, Shan Ul Haq, Huzifa Arshad, et al.
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 5
Prediction of motor function in patients with traumatic brain injury using genetic algorithms modified back propagation neural network: a data-based study
Hui Dang, Wenlong Su, Zhiqing Tang, et al.
Frontiers in Neuroscience (2023) Vol. 16
Open Access | Times Cited: 2
Machine learning application for prediction of surgical site infection after posterior cervical surgery
Keyu Lu, Yiting Tu, Shenkai Su, et al.
International Wound Journal (2023) Vol. 21, Iss. 4
Open Access | Times Cited: 2
Role of Artificial Intelligence (AI) in Surgery: Introduction, General Principles, and Potential Applications
Alberto Mangano, Valentina Valle, Nicolás H. Dreifuss, et al.
Surgical Technology Online (2020)
Closed Access | Times Cited: 4
Early Prediction of Sepsis Using Machine Learning Algorithms: A Review
N. Shanthi, A. Aadhishri, R.C. Suganthe, et al.
Communications in computer and information science (2024), pp. 113-125
Closed Access
Comparative Analysis of Machine Learning Models for Prediction of Acute Liver Injury in Sepsis Patients
Xiaochi Lu, Yi Chen, Gongping Zhang, et al.
Journal of Emergencies Trauma and Shock (2024) Vol. 17, Iss. 2, pp. 91-101
Open Access
Phenotyping cardiogenic shock that showed different clinical outcomes and responses to vasopressor use: a latent profile analysis from MIMIC-IV database
Yue Yu, Jin Rao, Qiumeng Xu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 1
PARSE: A personalized clinical time-series representation learning framework via abnormal offsets analysis
Ying An, Guanglei Cai, Xianlai Chen, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 242, pp. 107838-107838
Closed Access | Times Cited: 1
Prediction of Sepsis Disease Using Random Search to Optimize Hyperparameter Tuning Based on Lazy Predict Model
E. Laxmi Lydia, Sara A. Althubiti, C. S. S. Anupama, et al.
Smart innovation, systems and technologies (2023), pp. 351-367
Closed Access | Times Cited: 1
Machine learning identification of specific changes in myeloid cell phenotype during bloodstream infections
Christian Gosset, Jacques Foguenne, Mickaël Simul, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Identification of Distinct Clinical Phenotypes of Cardiogenic Shock Using Machine Learning Consensus Clustering Approach
Li Wang, Yufeng Zhang, Ren-qi Yao, et al.
Research Square (Research Square) (2023)
Open Access
Deep learning-based prediction of in-hospital mortality of sepsis
Yong Li, Zhenzhou Liu
Research Square (Research Square) (2023)
Open Access
An Agitation Sedation Level Prediction Model for ICU Patients
Pei-Yu Dai, Pei-Yi Lin, Ruey-Kai Shue, et al.
Research Square (Research Square) (2023)
Open Access
Deep Learning Model to Predict In-hospital Mortality of Newborns during Congenital Heart Disease Surgery
Nasmin Jiwani, Ketan Gupta, S. Velliangiri, et al.
The Open Bioinformatics Journal (2023) Vol. 16, Iss. 1
Open Access
Developing an Interpretable Machine Learning Model to Predict In-Hospital Mortality in Sepsis Patients: A Retrospective Study of MIMIC-IV
Shuhe Li, Xiaodong Song, Ka Yin Lui, et al.
Research Square (Research Square) (2022)
Open Access
Identification of Distinct Clinical Phenotypes of Cardiogenic Shock Using Machine Learning Consensus Clustering Approach
Li Wang, Yufeng Zhang, Ren-qi Yao, et al.
Research Square (Research Square) (2022)
Open Access

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