HIGHLIGHTS
- who: Carlos Figuera et al. from the Department of Telecommunication Engineering, Universidad Rey Juan, Madrid, Spain have published the research work: Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators, in the Journal: PLOS ONE | DOI:10.1371/journal.pone [0159654]. July 21, 2016 of /1371/
- what: This study evaluates VF-detection using from both OHCA patients and public Holter recordings. Within the AHA framework, this study explores the differences in the detection of Sh rhythms when public or OHCA data are used to optimize the algorithms. The analysis shows that . . .
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