Your browser doesn't support javascript.
loading
Machine learning for early detection of sepsis: an internal and temporal validation study.
Bedoya, Armando D; Futoma, Joseph; Clement, Meredith E; Corey, Kristin; Brajer, Nathan; Lin, Anthony; Simons, Morgan G; Gao, Michael; Nichols, Marshall; Balu, Suresh; Heller, Katherine; Sendak, Mark; O'Brien, Cara.
Affiliation
  • Bedoya AD; Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, North Carolina, USA.
  • Futoma J; Department of Statistics, Duke University, Durham, North Carolina, USA.
  • Clement ME; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.
  • Corey K; Department of Medicine, Division of Infectious Diseases, Duke University, Durham, North Carolina, USA.
  • Brajer N; Duke Institute for Health Innovation, Durham, North Carolina, USA.
  • Lin A; Duke University School of Medicine, Durham, North Carolina, USA.
  • Simons MG; Duke Institute for Health Innovation, Durham, North Carolina, USA.
  • Gao M; Duke University School of Medicine, Durham, North Carolina, USA.
  • Nichols M; Duke Institute for Health Innovation, Durham, North Carolina, USA.
  • Balu S; Duke University School of Medicine, Durham, North Carolina, USA.
  • Heller K; Duke Institute for Health Innovation, Durham, North Carolina, USA.
  • Sendak M; Duke University School of Medicine, Durham, North Carolina, USA.
  • O'Brien C; Duke Institute for Health Innovation, Durham, North Carolina, USA.
JAMIA Open ; 3(2): 252-260, 2020 Jul.
Article in En | MEDLINE | ID: mdl-32734166
Key words
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Language: En Journal: JAMIA Open Year: 2020 Type: Article Affiliation country: United States
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Language: En Journal: JAMIA Open Year: 2020 Type: Article Affiliation country: United States