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A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization
Title A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization. textový dokument (print) Author Lipták P. Co-authors Banovcin P. Rosoľanka R. Prokopič M. Kocan I. Žiačiková I. Uhrik P. Grendár Marián 1969 SAVMER - Ústav merania SAV SCOPUS RID ORCID Hyrdel R. Source document PeerJ. (2022), art. no. e13124 Language eng - English Country US - United States of America Document kind rozpis článkov z periodík (rbx) Citations MARTINEZ, J.A. - ALONSO-BERNALDEZ, M. - MARTINEZ-URBISTONDO, D. - VARGAS-NUNEZ, J.A. - DE MOLINA, A.R. - DAVALOS, A. - RAMOS-LOPEZ, O. Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases. In WORLD JOURNAL OF GASTROENTEROLOGY. ISSN 1007-9327, NOV 28 2022, vol. 28, no. 44, p. 6230-6248. Dostupné na: https://doi.org/10.3748/wjg.v28.i44.6230. LEE, K.S. - KIM, E.S. Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease. In DIAGNOSTICS. NOV 2022, vol. 12, no. 11. Dostupné na: https://doi.org/10.3390/diagnostics12112740. Category ADMA - Scientific papers in foreign impacted journals registered in Web of Sciences or Scopus Category of document (from 2022) V3 - Vedecký výstup publikačnej činnosti z časopisu Type of document článok Year 2022 Registered in WOS Registered in SCOPUS DOI 10.7717/peerj.13124 article
File name Access Size Downloaded Type License A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization.pdf available 4.3 MB 4 Publisher's version rok CC IF IF Q (best) JCR Av Jour IF Perc SJR SJR Q (best) CiteScore N rok vydania rok metriky IF IF Q (best) SJR SJR Q (best) 2022 2021 3.061 Q2 0.766 Q1
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