Concepedia

Machine learning can support dispatchers to better and faster recognize out-of-hospital cardiac arrest during emergency calls: A retrospective study

Fredrik Byrsell, Andreas Claesson, Mattias Ringh, Leif Svensson, Martin Jönsson, Per Nordberg, Sune Forsberg, Jacob Hollenberg, Anette Nord

Resuscitation · 2021 · 57 citations · 27 references

DOI Full text

Open access

Abstract

ML recognized a higher proportion of OHCA within the first minute compared with dispatchers and has the potential to be a supportive tool during emergency calls. The optimal FPR settings need to be evaluated in a prospective study.

References

27

Dermatologist-level classification of skin cancer with deep neural networks

Andre Esteva, Brett Kuprel, Roberto A. Novoa et al. · Nature · 2017 · 13K citations · Full text

Dermoscopic Image, Convolutional Neural Network, Deep Neural Networks +6

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Varun Gulshan, Lily Peng, Marc Coram et al. · JAMA · 2016 · 7.2K citations

Cardiac Arrest and Cardiopulmonary Resuscitation Outcome Reports

Ian Jacobs, Vinay Nadkarni · Circulation · 2004 · 2.5K citations · Full text

Trauma Resuscitation, Resuscitation Practice, Heart Failure +11

Clinically applicable deep learning for diagnosis and referral in retinal disease

Jeffrey De Fauw, Joseph R. Ledsam, Bernardino Romera‐Paredes et al. · Nature Medicine · 2018 · 2.5K citations

Convolutional Neural Network, Ocular Disease, Engineering +10

European Resuscitation Council Guidelines for Resuscitation 2010 Section 2. Adult basic life support and use of automated external defibrillators

Rudolph W. Koster, Michael Baubin, Leo Bossaert et al. · Resuscitation · 2010 · 1.6K citations · Full text

Neonatal Resuscitation, Trauma Resuscitation, Section 2 +10