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Cited by in F6Publishing
For: Jamshidi E, Asgary A, Tavakoli N, Zali A, Setareh S, Esmaily H, Jamaldini SH, Daaee A, Babajani A, Sendani Kashi MA, Jamshidi M, Jamal Rahi S, Mansouri N. Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU. Front Digit Health 2022;3:681608. [DOI: 10.3389/fdgth.2021.681608] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Barough SS, Safavi-naini SAA, Siavoshi F, Tamimi A, Ilkhani S, Akbari S, Ezzati S, Hatamabadi H, Pourhoseingholi MA. COVID-19 Mortality Risk Prediction using Clinical and Laboratory Examination: Machine Learning Approach for Implementation.. [DOI: 10.21203/rs.3.rs-2152771/v1] [Reference Citation Analysis]
2 Deng Y, Liu S, Wang Z, Wang Y, Jiang Y, Liu B. Explainable time-series deep learning models for the prediction of mortality, prolonged length of stay and 30-day readmission in intensive care patients. Front Med 2022;9. [DOI: 10.3389/fmed.2022.933037] [Reference Citation Analysis]
3 Gao J, Yang C, Heintz J, Barrows S, Albers E, Stapel M, Warfield S, Cross A, Sun J; N3C consortium. MedML: Fusing medical knowledge and machine learning models for early pediatric COVID-19 hospitalization and severity prediction. iScience 2022;25:104970. [PMID: 35992304 DOI: 10.1016/j.isci.2022.104970] [Reference Citation Analysis]
4 Nguyen XV, Dikici E, Candemir S, Ball RL, Prevedello LM. Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features. Tomography 2022;8:1791-1803. [DOI: 10.3390/tomography8040151] [Reference Citation Analysis]
5 Adamo S, Ambrosino P, Ricciardi C, Accardo M, Mosella M, Cesarelli M, d’Addio G, Maniscalco M. A Machine Learning Approach to Predict the Rehabilitation Outcome in Convalescent COVID-19 Patients. JPM 2022;12:328. [DOI: 10.3390/jpm12030328] [Reference Citation Analysis]