Visual assessment of interactions among resuscitation activity factors in out-of-hospital cardiopulmonary arrest using a machine learning model

HIGHLIGHTS

• who: Yasuyuki Kawai and colleagues from the Department of Emergency and Critical Care Medicine, Nara Medical University, Kashihara City, Nara, Japan have published the paper: Visual assessment of interactions among resuscitation activity factors in out-of-hospital cardiopulmonary arrest using a machine learning model, in the Journal: PLOS ONE of December/24,/2021
• what: To improve OHCA success rates this study assessed the prognostic interactions resulting from simultaneously modifying two prehospital factors using a trained machine learning model. Using this model the authors evaluated the prognostic impact of continuously and simultaneously varying the transport time . . .
  

   

  

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