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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 parsimonious multivariable predictive model of mortality risk in patients with Covid-19
Rita Murri, Jacopo Lenkowicz, C. Masciocchi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 18

Showing 18 citing articles:

Prognostic models in COVID-19 infection that predict severity: a systematic review
Chepkoech Buttia, Erand Llanaj, Hamidreza Raeisi‐Dehkordi, et al.
European Journal of Epidemiology (2023) Vol. 38, Iss. 4, pp. 355-372
Open Access | Times Cited: 35
Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review
Saeed Shakibfar, Fredrik Nyberg, Huiqi Li, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 16
Artificial intelligence in routine blood tests
Miguel A. Santos-Silva, Nuno Sousa, João Carlos Sousa
Frontiers in Medical Engineering (2024) Vol. 2
Open Access | Times Cited: 5
Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis
Ruiyao Chen, Jiayuan Chen, Sen Yang, et al.
International Journal of Medical Informatics (2023) Vol. 177, pp. 105151-105151
Closed Access | Times Cited: 12
A real-time integrated framework to support clinical decision making for covid-19 patients
Rita Murri, C. Masciocchi, Jacopo Lenkowicz, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 217, pp. 106655-106655
Open Access | Times Cited: 19
Improving the performance of machine learning algorithms for health outcomes predictions in multicentric cohorts
Roberta Moreira Wichmann, Fernando Timoteo Fernandes, Alexandre Dias Porto Chiavegatto Filho, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
Multidisciplinary Tumor Board Smart Virtual Assistant in Locally Advanced Cervical Cancer: A Proof of Concept
Gabriella Macchia, Gabriella Ferrandina, Stefano Patarnello, et al.
Frontiers in Oncology (2022) Vol. 11
Open Access | Times Cited: 12
The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis
Yu Xin, Hongxu Li, Yuxin Zhou, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 7
Drivers and forecasts of multiple waves of the coronavirus disease 2019 pandemic: A systematic analysis based on an interpretable machine learning framework
Zicheng Cao, Zekai Qiu, Feng Tang, et al.
Transboundary and Emerging Diseases (2022) Vol. 69, Iss. 5
Open Access | Times Cited: 7
Machine-learning-derived predictive score for early estimation of COVID-19 mortality risk in hospitalized patients
Alba González–Cebrián, Joan Borràs‐Ferrís, Juan Pablo Ordovás Baines, et al.
PLoS ONE (2022) Vol. 17, Iss. 9, pp. e0274171-e0274171
Open Access | Times Cited: 7
Fib-4 score is able to predict intra-hospital mortality in 4 different SARS-COV2 waves
Luca Miele, Marianxhela Dajko, M. Savino, et al.
Internal and Emergency Medicine (2023) Vol. 18, Iss. 5, pp. 1415-1427
Open Access | Times Cited: 3
Severity of Illness Scores and Biomarkers for Prognosis of Patients with Coronavirus Disease 2019
Rodrigo Cavallazzi, James Bradley, Thomas Chandler, et al.
Seminars in Respiratory and Critical Care Medicine (2023) Vol. 44, Iss. 01, pp. 075-090
Closed Access | Times Cited: 2
Cardiovascular and Renal Comorbidities Included into Neural Networks Predict the Outcome in COVID-19 Patients Admitted to an Intensive Care Unit: Three-Center, Cross-Validation, Age- and Sex-Matched Study
Е. А. Овчаренко, Anton G. Kutikhin, О. В. Груздева, et al.
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 2, pp. 39-39
Open Access | Times Cited: 2
Metabolic syndrome prediction models using only lifestyle information based on nationwide survey data
Seunghyeon Yu, Haeun Lee, Ilha Yune, et al.
Research Square (Research Square) (2024)
Open Access
A hybrid machine learning model for predicting gene expression from epigenetics across fungal species
Laura D. Weinstock, J. Schambach, Anna Fisher, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records (Preprint)
Tom Velez, Xiaoshan Wang, Brian T. Garibaldi, et al.
(2023)
Open Access
Identification and Prediction of Clinical Phenotypes in Hospitalized COVID-19 Patients: A Step towards Precision Medicine (Preprint)
Tom Velez, Xiaoshan Wang, Brian T. Garibaldi, et al.
JMIR Formative Research (2023) Vol. 7, pp. e46807-e46807
Open Access
Artificial Intelligence and Deep Phenotyping in COVID-19
Luciano Giacò, Bertrand De Meulder, Vincenzo Valentini, et al.
Springer eBooks (2023), pp. 121-129
Closed Access
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