AIMC Topic: Emergency Medical Dispatch

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Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN).

Scientific reports Apr 24, 2025
The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and s...
Humans Neural Networks, Computer Deep Learning Support Vector Machine Emergency Medical Services Ambulances Emergency Medical Dispatch
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Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial.

JAMA network open Jan 4, 2021
IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.
Humans Machine Learning Female Aged Male Denmark Double-Blind Method Out-of-Hospital Cardiac Arrest Emergency Medical Dispatch
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Machine learning as a supportive tool to recognize cardiac arrest in emergency calls.

Resuscitation Jan 18, 2019
BACKGROUND: Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. We examined whether a machine lear...
Humans Machine Learning Retrospective Studies Female Aged Aged, 80 and over Male Middle Aged Time Factors ROC Curve Emergency Medical Services Cardiopulmonary Resuscitation Out-of-Hospital Cardiac Arrest Emergency Medical Dispatch Emergency Medical Service Communication Systems
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