Machine learning-based approach to guide the choice between baricitinib and tocilizumab in critical COVID-19 pneumonia treatment: a retrospective cohort study.
Saved in:
| Title: | Machine learning-based approach to guide the choice between baricitinib and tocilizumab in critical COVID-19 pneumonia treatment: a retrospective cohort study. |
|---|---|
| Authors: | Chang E; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Kim MS; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.; ImpriMedKorea, Inc., Seoul, Republic of Korea., Park SY; Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea., Kwon K; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Jang HM; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Lim SY; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Bae S; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Jung J; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Kim MJ; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Chong YP; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Lee SO; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Choi SH; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Kim YS; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Choi G; ImpriMedKorea, Inc., Seoul, Republic of Korea., Lim S; ImpriMed, Inc., Mountain View, CA, United States., Koo J; ImpriMedKorea, Inc., Seoul, Republic of Korea.; ImpriMed, Inc., Mountain View, CA, United States.; Department of Chemical Engineering, Hongik University, Seoul, Republic of Korea., Kim SH; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. |
| Source: | Frontiers in medicine [Front Med (Lausanne)] 2026 Jan 07; Vol. 12, pp. 1734109. Date of Electronic Publication: 2026 Jan 07 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41574379 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Machine learning-based approach to guide the choice between baricitinib and tocilizumab in critical COVID-19 pneumonia treatment: a retrospective cohort study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Chang+E%22">Chang E</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+MS%22">Kim MS</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.; ImpriMedKorea, Inc., Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Park+SY%22">Park SY</searchLink>; Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kwon+K%22">Kwon K</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Jang+HM%22">Jang HM</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lim+SY%22">Lim SY</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Bae+S%22">Bae S</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Jung+J%22">Jung J</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+MJ%22">Kim MJ</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Chong+YP%22">Chong YP</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+SO%22">Lee SO</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Choi+SH%22">Choi SH</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+YS%22">Kim YS</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Choi+G%22">Choi G</searchLink>; ImpriMedKorea, Inc., Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lim+S%22">Lim S</searchLink>; ImpriMed, Inc., Mountain View, CA, United States.<br /><searchLink fieldCode="AU" term="%22Koo+J%22">Koo J</searchLink>; ImpriMedKorea, Inc., Seoul, Republic of Korea.; ImpriMed, Inc., Mountain View, CA, United States.; Department of Chemical Engineering, Hongik University, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+SH%22">Kim SH</searchLink>; Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101648047%22">Frontiers in medicine</searchLink> [Front Med (Lausanne)] 2026 Jan 07; Vol. 12, pp. 1734109. <i>Date of Electronic Publication: </i>2026 Jan 07 (<i>Print Publication: </i>2025). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Media+S%2EA%22">Frontiers Media S.A </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101648047 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2296-858X (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222296858X%22">2296858X </searchLink><i>NLM ISO Abbreviation: </i>Front Med (Lausanne) <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41574379 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fmed.2025.1734109 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 1734109 Titles: – TitleFull: Machine learning-based approach to guide the choice between baricitinib and tocilizumab in critical COVID-19 pneumonia treatment: a retrospective cohort study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chang E – PersonEntity: Name: NameFull: Kim MS – PersonEntity: Name: NameFull: Park SY – PersonEntity: Name: NameFull: Kwon K – PersonEntity: Name: NameFull: Jang HM – PersonEntity: Name: NameFull: Lim SY – PersonEntity: Name: NameFull: Bae S – PersonEntity: Name: NameFull: Jung J – PersonEntity: Name: NameFull: Kim MJ – PersonEntity: Name: NameFull: Chong YP – PersonEntity: Name: NameFull: Lee SO – PersonEntity: Name: NameFull: Choi SH – PersonEntity: Name: NameFull: Kim YS – PersonEntity: Name: NameFull: Choi G – PersonEntity: Name: NameFull: Lim S – PersonEntity: Name: NameFull: Koo J – PersonEntity: Name: NameFull: Kim SH IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 01 Text: 2026 Jan 07 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 2296-858X Numbering: – Type: volume Value: 12 Titles: – TitleFull: Frontiers in medicine Type: main |
| ResultId | 1 |