Investigating the association of acute kidney injury (AKI) with COVID-19 mortality using data-mining scheme.
Creators
- 1. Emergency Medicine Department, Deputy of Treatment, Faculty of Medicine, Mashhad University of Medical Science, Mashed, Iran.
- 2. Department of Nursing, Faculty of Nursing and Midwifery, Mashhad Medical Sciences, Islamic Azad University, Mashhad, Iran.
- 3. Islamic Azad University
- 4. Medical Student Research Committee, Sabzevar University of Medical Science, Sabzevar, Iran.
- 5. Department of Epidemiology & Biostatistics, School of public health, Tehran University of Medical Sciences, Tehran, Iran.
- 6. Tehran University of Medical Sciences
- 7. Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran; International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran. Electronic address: talkhin3@mums.ac.ir.
Publication Details
Journal article
Journal:
Diagnostic microbiology and infectious disease
Publisher:
Elsevier BV
ISSN:
18790070
Volume:
107
Pages:
116026-116026
References
Bagley . Logistic regression in the medical literature:: standards for use and r...
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Moulaei . Predicting mortality of COVID-19 patients based on data mining techniq...
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Sahebhonar . A comparison of three research methods: logistic regression, decisi...
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Lin . Risk factors and prognosis for COVID-19-induced acute kidney injury: a met...
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Cheng . The incidence, risk factors, and prognosis of acute kidney injury in adu...
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Showing first 5 of 27 references.
Scholarly Citations
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