Erzincan Binali Yıldırım ÜniversitesiErzincan Binali Yıldırım ÜniversitesiAçık Erişim Arşivi · RDL Open

Corrigendum to “LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19” [MethodsX 10 (2023) 102194] (MethodsX (2023) 10, (S2215016123001942), (10.1016/j.mex.2023.102194))

CorrectionAçık Erişim

Özet

The authors regret that they forgot to write the ethical approval number of the article. This study was approved by Erzincan Binali Yıldırım University Non-Interventional Clinical Research Ethics Committee (Reference No: 27.05.2022, 11-14) The authors would like to apologize for any inconvenience caused. © 2024 The Authors

Anahtar Kelimeler

erratumhumanmale
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/10876Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.mex.2024.103103Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorHuyut, Mehmet Tahir
dc.contributor.authorVelichko, Andrei
dc.date.accessioned2026-10-18T20:25:59.727574378Z
dc.date.available2026-10-18T20:25:59.727574378Z
dc.date.issued2025
dc.description.abstractThe authors regret that they forgot to write the ethical approval number of the article. This study was approved by Erzincan Binali Yıldırım University Non-Interventional Clinical Research Ethics Committee (Reference No: 27.05.2022, 11-14) The authors would like to apologize for any inconvenience caused. © 2024 The Authors
dc.identifier.doi10.1016/j.mex.2024.103103
dc.identifier.eissn2215-0161
dc.identifier.issn2215-0161
dc.identifier.pmcidPMC11719400
dc.identifier.pmid39802435
dc.identifier.scopus2-s2.0-85212109883
dc.identifier.startpage103103
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/10876
dc.identifier.volume14
dc.identifier.wosWOS:001417510900001
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofMethodsX
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjecterratum
dc.subjecthuman
dc.subjectmale
dc.titleCorrigendum to “LogNNet model as a fast, simple and economical AI instrument in the diagnosis and prognosis of COVID-19” [MethodsX 10 (2023) 102194] (MethodsX (2023) 10, (S2215016123001942), (10.1016/j.mex.2023.102194))
dc.typeCorrection
dspace.entity.typePublication
rdl.citation.scopus0
rdl.citation.wos0
rdl.departmentDepartment of Biostatistics and Medical Informatics, Faculty of Medicine, Erzincan Binali Yıldırım University, 24000 Erzincan, Turkey.
rdl.oa.statusgold
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexEmerging Sources Citation Index (ESCI)