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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:

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records
Hans‐Christian Thorsen‐Meyer, Annelaura Bach Nielsen, Anna Pors Nielsen, et al.
The Lancet Digital Health (2020) Vol. 2, Iss. 4, pp. e179-e191
Open Access | Times Cited: 257

Showing 1-25 of 257 citing articles:

AI in health and medicine
Pranav Rajpurkar, Emma Chen, Oishi Banerjee, et al.
Nature Medicine (2022) Vol. 28, Iss. 1, pp. 31-38
Closed Access | Times Cited: 1395
Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Hui Wen Loh, Chui Ping Ooi, Silvia Seoni, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107161-107161
Open Access | Times Cited: 419
Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 195
A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories
Davide Placido, Bo Yuan, Jessica Xin Hjaltelin, et al.
Nature Medicine (2023) Vol. 29, Iss. 5, pp. 1113-1122
Open Access | Times Cited: 149
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
Artificial Intelligence and Early Detection of Pancreatic Cancer
Barbara Kenner, Suresh T. Chari, David P. Kelsen, et al.
Pancreas (2021) Vol. 50, Iss. 3, pp. 251-279
Open Access | Times Cited: 112
Artificial Intelligence in Critical Care Medicine
Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont
Critical Care (2022) Vol. 26, Iss. 1
Open Access | Times Cited: 92
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
Flavio Di Martino, Franca Delmastro
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5261-5315
Open Access | Times Cited: 85
Modern views of machine learning for precision psychiatry
Zhe Chen, Prathamesh Kulkarni, Isaac R. Galatzer‐Levy, et al.
Patterns (2022) Vol. 3, Iss. 11, pp. 100602-100602
Open Access | Times Cited: 83
Time Series Prediction Using Deep Learning Methods in Healthcare
Mohammad Amin Morid, Olivia R. Liu Sheng, Joseph C. Dunbar
ACM Transactions on Management Information Systems (2022) Vol. 14, Iss. 1, pp. 1-29
Open Access | Times Cited: 70
Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine
Ahmad Chaddad, Qizong Lu, Jiali Li, et al.
IEEE/CAA Journal of Automatica Sinica (2023) Vol. 10, Iss. 4, pp. 859-876
Open Access | Times Cited: 45
Explainable and interpretable artificial intelligence in medicine: a systematic bibliometric review
Maria Frasca, Davide La Torre, Gabriella Pravettoni, et al.
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 38
Position Paper on the Reporting of Norepinephrine Formulations in Critical Care from the Society of Critical Care Medicine and European Society of Intensive Care Medicine Joint Task Force
Patrick M. Wieruszewski, Marc Léone, Benjamin Skov Kaas‐Hansen, et al.
Critical Care Medicine (2024) Vol. 52, Iss. 4, pp. 521-530
Open Access | Times Cited: 25
AutoScore: A Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records
Feng Xie, Bibhas Chakraborty, Marcus Eng Hock Ong, et al.
JMIR Medical Informatics (2020) Vol. 8, Iss. 10, pp. e21798-e21798
Open Access | Times Cited: 110
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Feng Xie, Han Yuan, Yilin Ning, et al.
Journal of Biomedical Informatics (2021) Vol. 126, pp. 103980-103980
Open Access | Times Cited: 75
Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data
Osvald Nitski, Amirhossein Azhie, Fakhar Ali Qazi Arisar, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 5, pp. e295-e305
Open Access | Times Cited: 74
Ensembling Classical Machine Learning and Deep Learning Approaches for Morbidity Identification From Clinical Notes
Vivek Kumar, Diego Reforgiato Recupero, Daniele Riboni, et al.
IEEE Access (2020) Vol. 9, pp. 7107-7126
Open Access | Times Cited: 71
Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study
Alexander Bonde, Kartik M. Varadarajan, Nicholas Bonde, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 8, pp. e471-e485
Open Access | Times Cited: 68
Computational Models for Clinical Applications in Personalized Medicine—Guidelines and Recommendations for Data Integration and Model Validation
Catherine Bjerre Collin, Tom Gebhardt, Martin Golebiewski, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 2, pp. 166-166
Open Access | Times Cited: 59
ConSIG: consistent discovery of molecular signature from OMIC data
Fengcheng Li, Jiayi Yin, Mingkun Lu, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Closed Access | Times Cited: 59
Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study
Rahuldeb Sarkar, Christopher S. Martin, Heather Mattie, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 4, pp. e241-e249
Open Access | Times Cited: 57
Comparative analysis of explainable machine learning prediction models for hospital mortality
Eline Stenwig, Giampiero Salvi, Pierluigi Salvo Rossi, et al.
BMC Medical Research Methodology (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 44
Machine and deep learning for longitudinal biomedical data: a review of methods and applications
Anna Cascarano, Jordi Mur-Petit, Jerónimo Hernández-González, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. S2, pp. 1711-1771
Open Access | Times Cited: 29
Machine Learning–Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study
Xiao-Qin Luo, Yixin Kang, Shao-Bin Duan, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e41142-e41142
Open Access | Times Cited: 24
Current methods in explainable artificial intelligence and future prospects for integrative physiology
Bettina Finzel
Pflügers Archiv - European Journal of Physiology (2025)
Open Access | Times Cited: 1
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