A smart-technology wearable wristband device may be able to automatically detect cardiac arrest, which could lead to faster medical assistance and increased survival odds when cardiac arrest occurs ...
Results from the RAPID-MIRACLE trial have found, for the first time, that the widely used MIRACLE 2 risk score can be applied outside a hospital setting to accurately predict brain injury following a ...
A machine learning algorithm running on a smartwatch demonstrated the ability to detect sudden loss of pulse with high specificity (99.99%) and moderate sensitivity (67.23%), according to a study led ...
To address out-of-hospital cardiac arrest, Osaka Metropolitan University researchers developed a new scoring method that uses only data available from prehospital resuscitations to accurately predict ...
Clinician-scientists in the Smidt Heart Institute at Cedars-Sinai developed a clinical algorithm that, for the first time, distinguishes between treatable sudden cardiac arrest and untreatable forms ...
Machine learning algorithms for predicting days of high incidence for out-of-hospital cardiac arrest
Predicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA ...
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