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Multiomics single timepoint measurements to predict severe COVID-19 - Authors' reply.
Garapati, Kishore; Byeon, Seul Kee; Walsh, Jesse R; Jenkinson, Garrett; Cattaneo, Roberto; O'Horo, John C; Badley, Andrew D; Pandey, Akhilesh.
Affiliation
  • Garapati K; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka, India; Manipal Academy of Higher Education, Manipal, Karnataka, India.
  • Byeon SK; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
  • Walsh JR; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
  • Jenkinson G; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.
  • Cattaneo R; Department of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • O'Horo JC; Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Badley AD; Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA.
  • Pandey A; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: pandey.akhilesh@mayo.edu.
Lancet Digit Health ; 5(2): e57, 2023 02.
Article in En | MEDLINE | ID: mdl-36707188
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Lancet Digit Health Year: 2023 Document type: Article Affiliation country: India Country of publication: United kingdom
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Lancet Digit Health Year: 2023 Document type: Article Affiliation country: India Country of publication: United kingdom