AIMC Topic: Emergency Medical Services
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Machine learning to improve predictive performance of prehospital early warning scores.
Scientific reports
Jul 1, 2025
Early warning scores are used to assess acute patients' risk of being in a critical situation, allowing for early appropriate treatment, avoiding critical outcomes. The early warning scores use changes in vital signs to provide an assessment, however...
Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.
BMJ health & care informatics
Jun 6, 2025
OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). Distinguishing true NSTE-ACS from non-cardiac chest pain based solely on the EC...
Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.
BMC medical informatics and decision making
Jun 3, 2025
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...
A Machine Learning Trauma Triage Model for Critical Care Transport.
JAMA network open
Jun 2, 2025
IMPORTANCE: Under austere prehospital conditions, rapid classification of injured patients for intervention or transport is essential for providing lifesaving care. Discerning which patients need care most urgently further allows for optimal allocati...
Enhancing clinical decision support with physiological waveforms - A multimodal benchmark in emergency care.
Computers in biology and medicine
Apr 30, 2025
BACKGROUND: AI-driven prediction algorithms have the potential to enhance emergency medicine by enabling rapid and accurate decision-making regarding patient status and potential deterioration. However, the integration of multimodal data, including r...
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...
Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems.
International journal of injury control and safety promotion
Apr 11, 2025
Traffic injuries are a major public health concern globally. This study uses machine learning (ML) and geographic analysis to analyse road traffic fatalities and improve traffic safety in Nakhon Ratchasima Province, Thailand. Data on road traffic fat...
Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management.
Journal of medical Internet research
Apr 10, 2025
In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a promising future, offering potential improvements in processes such as triage, decision support, and resource optimization. However, the effectivenes...
Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.
Scientific reports
Apr 3, 2025
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sou...
Evaluating the predictive performance of different data sources to forecast overdose deaths at the neighborhood level with machine learning in Rhode Island.
Preventive medicine
Mar 29, 2025
OBJECTIVES: To evaluate the predictive performance of different data sources to forecast fatal overdose in Rhode Island neighborhoods, with the goal of providing a template for other jurisdictions interested in predictive analytics to direct overdose...
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