AIMC Topic: Emergency Medical Services

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Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

Computational intelligence and neuroscience
Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency ma...

Demand Forecast Using Data Analytics for the Preallocation of Ambulances.

IEEE journal of biomedical and health informatics
The objective of prehospital emergency medical services (EMSs) is to have a short response time. By increasing the operational efficiency, the survival rate of patients could potentially be increased. The geographic information system (GIS) is introd...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

Annals of emergency medicine
STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insights into the out-of-hospital pathways of patients with stroke. This study explored the ability of EMCC...

Evaluating large language models as clinical laboratory test recommenders in primary and emergency care: a crucial step in clinical decision making.

Clinical chemistry and laboratory medicine
OBJECTIVES: Large language models (LLMs), such as OpenAI's GPT-4o, have demonstrated considerable promise in transforming clinical decision support systems. In this study, we focused on a single but crucial task of clinical decision-making: laborator...

ASSOCIATIONS BETWEEN HEART RATE VARIABILITY AND NEED FOR LIFESAVING INTERVENTION IN A LARGE HELICOPTER EMS SERVICE.

Shock (Augusta, Ga.)
Background : Heart rate variability (HRV) measures give insight into the autonomic regulation of cardiac function in healthy and critically ill patients. The ease and predictive potential of HRV measures may be valuable in optimizing prehospital tria...

Assessment and Integration of Large Language Models for Automated Electronic Health Record Documentation in Emergency Medical Services.

Journal of medical systems
Automating Electronic Health Records (EHR) documentation can significantly reduce the burden on care providers, particularly in emergency care settings where rapid and accurate record-keeping is crucial. A critical aspect of this automation involves ...

Improving prediction accuracy of hospital arrival vital signs using a multi-output machine learning model: a retrospective study of JSAS-registry data.

BMC emergency medicine
BACKGROUND: Critically ill patients can deteriorate rapidly; therefore, prompt prehospital interventions and seamless transition to in-hospital care upon arrival are crucial for improving survival. In Japan, helicopter emergency medical services (HEM...

Prehospital triage of trauma patients: predicting major surgery using artificial intelligence as decision support.

The British journal of surgery
BACKGROUND: Matching the necessary resources and facilities to attend to the needs of trauma patients is traditionally performed by clinicians using criteria-directed triage protocols. In the present study, it was hypothesized that an artificial inte...

Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery.

Studies in health technology and informatics
AIM: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)...