AIMC Topic: Emergency Medical Services
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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
Aug 22, 2024
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)...
Artificial intelligence and emergency services: We need to take a step forward.
Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
Apr 1, 2024
Social Determinants of Health in EMS Records: A Mixed-methods Analysis Using Natural Language Processing and Qualitative Content Analysis.
The western journal of emergency medicine
Sep 1, 2023
Social determinants of health (SDoH) are known to impact the health and well-being of patients. However, information regarding them is not always collected in healthcare interactions, and healthcare professionals are not always well-trained or equip...
Ethical Perspectives on Implementing AI to Predict Mortality Risk in Emergency Department Patients: A Qualitative Study.
Studies in health technology and informatics
May 18, 2023
Artificial intelligence (AI) is predicted to improve health care, increase efficiency and save time and recourses, especially in the context of emergency care where many critical decisions are made. Research shows the urgent need to develop principle...
Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury.
The journal of trauma and acute care surgery
Jan 1, 2022
BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study a...
Brain Injuries, Traumatic
Emergency Medical Services
Registries
Hospital Mortality
Decision Support Systems, Clinical
Guideline Adherence
Practice Guidelines as Topic
France
Shock, Hemorrhagic
Trauma Severity Indices
Patient Care Bundles
Critical Care
Quality Improvement
Humans
Adult
Male
Machine Learning
Female
Predicting outcomes after trauma: Prognostic model development based on admission features through machine learning.
Medicine
Dec 10, 2021
In an overcrowded emergency department (ED), trauma surgeons and emergency physicians need an accurate prognostic predictor for critical decision-making involving patients with severe trauma. We aimed to develope a machine learning-based early progno...
Development of a field artificial intelligence triage tool: Confidence in the prediction of shock, transfusion, and definitive surgical therapy in patients with truncal gunshot wounds.
The journal of trauma and acute care surgery
Jun 1, 2021
BACKGROUND: In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence reporting. We therefore set out to develop and test a machine learning algorithm that can overcome ...
Characterizing Opioid Overdoses Using Emergency Medical Services Data : A Case Definition Algorithm Enhanced by Machine Learning.
Public health reports (Washington, D.C. : 1974)
Jan 1, 2021
OBJECTIVES: Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (...
[Challenges of digitalization in trauma care].
Der Unfallchirurg
Nov 1, 2020
The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibilities that could help to sustainably improve the treatment of severe injuries in the future with the...
Emergency Clinical Procedure Detection With Deep Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Information about a patient's state is critical for hospitals to provide timely care and treatment. Prior work on improving the information flow from emergency medical services (EMS) to hospitals demonstrated the potential of using automated algorith...
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