[HTML][HTML] Artificial Intelligence in Emergency Medicine. A Systematic Literature Review.
K Piliuk, S Tomforde - International Journal of Medical Informatics, 2023 - Elsevier
Motivation and objective: Emergency medicine is becoming a popular application area for
artificial intelligence methods but remains less investigated than other healthcare branches …
artificial intelligence methods but remains less investigated than other healthcare branches …
The potential of new prediction models for emergency medical dispatch prioritisation of patients with chest pain: a cohort study
K Wibring, M Lingman, J Herlitz, A Bång - Scandinavian journal of trauma …, 2022 - Springer
Objectives To develop emergency medical dispatch (EMD) centre prediction models with
high sensitivity and satisfying specificity to identify high-priority patients and patients suitable …
high sensitivity and satisfying specificity to identify high-priority patients and patients suitable …
Modified sequential organ failure assessment score vs. early warning scores in prehospital care to predict major adverse cardiac events in acute cardiovascular …
E Castro Portillo, R López-Izquierdo… - Journal of …, 2023 - mdpi.com
(1) Background: The Modified Sequential Organ Failure Assessment (mSOFA) is an Early
Warning Score (EWS) that has proven to be useful in identifying patients at high risk of …
Warning Score (EWS) that has proven to be useful in identifying patients at high risk of …
Consequences of different cut-off values for high-sensitivity cardiac troponin for risk stratification of patients suspected for NSTE-ACS with a modified HEART score
RT Tolsma, MJ Fokkert, JP Ottervanger… - Future …, 2023 - Taylor & Francis
Aim: This study aims to enhance prehospital risk assessment for suspected non-ST-
elevation acute coronary syndrome (NSTE-ACS) patients using the HEART-score. By …
elevation acute coronary syndrome (NSTE-ACS) patients using the HEART-score. By …
The development of a decision support tool in the prehospital setting for acute chest pain–a study protocol for an observational study (BRIAN2)
E Lökholm, C Magnusson, J Herlitz… - Scandinavian Journal of …, 2025 - Springer
Introduction Chest pain is one of the most common reasons for contacting the emergency
medical services (EMS). It is difficult for EMS personnel to distinguish between patients …
medical services (EMS). It is difficult for EMS personnel to distinguish between patients …
The performance of screening tools and use of blood analyses in prehospital identification of sepsis patients and patients suitable for non-conveyance-an …
A Olander, L Frick, J Johansson, K Wibring - BMC Emergency Medicine, 2024 - Springer
Background Early recognition of sepsis by the EMS (Emergency Medical Services), along
with communicating this concern to the emergency department, could improve patient …
with communicating this concern to the emergency department, could improve patient …
Warning symptoms associated with imminent sudden cardiac arrest: a population-based case-control study with external validation
K Reinier, B Dizon, H Chugh, Z Bhanji… - The Lancet Digital …, 2023 - thelancet.com
Background Sudden cardiac arrest is a global public health problem with a mortality rate of
more than 90%. Prearrest warning symptoms could be harnessed using digital technology to …
more than 90%. Prearrest warning symptoms could be harnessed using digital technology to …
Clinical presentation in EMS patients with acute chest pain in relation to sex, age and medical history: prospective cohort study
K Wibring, M Lingman, J Herlitz, H Pettersson… - BMJ open, 2022 - bmjopen.bmj.com
Objective To assess symptom presentation related to age, sex and previous medical history
in patients with chest pain. Design Prospective observational cohort study. Setting Two …
in patients with chest pain. Design Prospective observational cohort study. Setting Two …
[HTML][HTML] Development of a prediction model for emergency medical service witnessed traumatic out-of-hospital cardiac arrest: A multicenter cohort study
Background/Purpose To develop a prediction model for emergency medical technicians
(EMTs) to identify trauma patients at high risk of deterioration to emergency medical service …
(EMTs) to identify trauma patients at high risk of deterioration to emergency medical service …
Deep Evidential Doctor
A Ashfaq - 2022 - diva-portal.org
Recent years have witnessed an unparalleled surge in deep neural networks (DNNs)
research, surpassing traditional machine learning (ML) and statistical methods on …
research, surpassing traditional machine learning (ML) and statistical methods on …