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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:

Interpretable Machine Learning for Early Prediction of Prognosis in Sepsis: A Discovery and Validation Study
Chang Hu, Lu Li, Weipeng Huang, et al.
Infectious Diseases and Therapy (2022) Vol. 11, Iss. 3, pp. 1117-1132
Open Access | Times Cited: 91

Showing 1-25 of 91 citing articles:

Investigation on explainable machine learning models to predict chronic kidney diseases
Samit Kumar Ghosh, Ahsan H. Khandoker
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 15
Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers
Guyu Zhang, Fei Shao, Yuan Wei, et al.
European journal of medical research (2024) Vol. 29, Iss. 1
Open Access | Times Cited: 13
Prediction of Sepsis Mortality in ICU Patients Using Machine Learning Methods
Jiayi Gao, Yu‐Ying Lu, Negin Ashrafi, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 11
Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease
Xunliang Li, Zhijuan Wang, Wenman Zhao, et al.
Renal Failure (2024) Vol. 46, Iss. 1
Open Access | Times Cited: 9
Explainable artificial intelligence (XAI) for predicting the need for intubation in methanol-poisoned patients: a study comparing deep and machine learning models
Khadijeh Moulaei, Mohammad Reza Afrash, Mohammad Parvin, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia
Jian‐Jun Wei, Heshan Cao, Mingling Peng, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0316526-e0316526
Open Access | Times Cited: 1
Application of interpretable machine learning for early prediction of prognosis in acute kidney injury
Chang Hu, Qing Tan, Qinran Zhang, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 2861-2870
Open Access | Times Cited: 30
Deep learning-based prediction of in-hospital mortality for sepsis
Yong Li, Liu Zhenzhou
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Prediction of sepsis mortality in ICU patients using machine learning methods
Jiayi Gao, Yu‐Ying Lu, Negin Ashrafi, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 7
Explainable Machine-Learning Model for Prediction of In-Hospital Mortality in Septic Patients Requiring Intensive Care Unit Readmission
Chang Hu, Lu Li, Yiming Li, et al.
Infectious Diseases and Therapy (2022) Vol. 11, Iss. 4, pp. 1695-1713
Open Access | Times Cited: 24
Machine learning-based prediction of in-ICU mortality in pneumonia patients
Eun‐Tae Jeon, Hyo Jin Lee, Tae Yun Park, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 16
Explainable artificial intelligence model for mortality risk prediction in the intensive care unit: a derivation and validation study
Chang Hu, Chao Gao, Tianlong Li, et al.
Postgraduate Medical Journal (2024) Vol. 100, Iss. 1182, pp. 219-227
Closed Access | Times Cited: 5
Explainable machine learning in outcome prediction of high-grade aneurysmal subarachnoid hemorrhage
Lei Shu, Hua Yan, Yanze Wu, et al.
Aging (2024), pp. 4654-4669
Open Access | Times Cited: 5
Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a National cohort study of 52,707 cases
M. Lei, Taojin Feng, Min Chen, et al.
International Journal of Surgery (2024)
Open Access | Times Cited: 5
Machine learning-based evaluation of application value of traditional Chinese medicine clinical index and pulse wave parameters in the diagnosis of polycystic ovary syndrome
Jiekee Lim, Jieyun Li, Xiao Feng, et al.
European Journal of Integrative Medicine (2023) Vol. 64, pp. 102311-102311
Open Access | Times Cited: 12
Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis
Yan Zhang, Weiwei Xu, Ping Yang, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 12
Developing an Interpretable Machine Learning Model to Predict in-Hospital Mortality in Sepsis Patients: A Retrospective Temporal Validation Study
Shuhe Li, Ruoxu Dou, Xiaodong Song, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 3, pp. 915-915
Open Access | Times Cited: 11
Machine learning algorithm to predict the in-hospital mortality in critically ill patients with chronic kidney disease
Xunliang Li, Yuyu Zhu, Wenman Zhao, et al.
Renal Failure (2023) Vol. 45, Iss. 1
Open Access | Times Cited: 11
Association between the triglyceride glucose index and length of hospital stay in patients with heart failure and type 2 diabetes in the intensive care unit: a retrospective cohort study
Kai Zhang, Yu Han, Gao Yu, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 4
Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making
Cherng Chia Yang, Ching Fu Wang, Wei Lin, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 4
Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit
Baojie Mao, Lichao Ling, Yuhang Pan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Early sepsis mortality prediction model based on interpretable machine learning approach: development and validation study
Yiping Wang, Zhihong Gao, Yang Zhang, et al.
Internal and Emergency Medicine (2024)
Open Access | Times Cited: 4
Prediction of mortality in intensive care unit with short-term heart rate variability: Machine learning-based analysis of the MIMIC-III database
Lexin Huang, Zixuan Dou, Fang Fang, et al.
Computers in Biology and Medicine (2025) Vol. 186, pp. 109635-109635
Closed Access
EHR-ML: A Data-Driven Framework for Designing Machine Learning Applications with Electronic Health Records
Yashpal Ramakrishnaiah, Nenad Macesic, Geoffrey I. Webb, et al.
International Journal of Medical Informatics (2025), pp. 105816-105816
Open Access
SOAR-ML: Synthetic Optimization and Augmentation for Robust Machine Learning in Oral Cancer Prediction
Akhil Chintalapati, Aparajita Senapati, Siddharth Pal, et al.
Communications in computer and information science (2025), pp. 174-187
Closed Access
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