Artificial intelligence in clinical decision support: a focused literature survey
Objectives: This survey analyses the latest literature contributions to clinical decision support
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …
Artificial intelligence and machine learning in prehospital emergency care: A scoping review
ML Chee, ML Chee, H Huang, K Mazzochi, K Taylor… - Iscience, 2023 - cell.com
Our scoping review provides a comprehensive analysis of the landscape of artificial
intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field …
intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field …
Deep neural network approach for continuous ECG‐based automated external defibrillator shock advisory system during cardiopulmonary resuscitation
S Hajeb‐M, A Cascella, M Valentine… - Journal of the American …, 2021 - Am Heart Assoc
Background Because chest compressions induce artifacts in the ECG, current automated
external defibrillators instruct the user to stop cardiopulmonary resuscitation (CPR) while an …
external defibrillators instruct the user to stop cardiopulmonary resuscitation (CPR) while an …
Rhythm analysis during cardiopulmonary resuscitation using convolutional neural networks
Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG
that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The …
that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The …
Multimodal algorithms for the classification of circulation states during out-of-hospital cardiac arrest
Goal: Identifying the circulation state during out-of-hospital cardiac arrest (OHCA) is
essential to determine what life-saving therapies to apply. Currently algorithms discriminate …
essential to determine what life-saving therapies to apply. Currently algorithms discriminate …
Automatic cardiac rhythm classification with concurrent manual chest compressions
Electrocardiogram (EKG) based classification of out-of-hospital cardiac arrest (OHCA)
rhythms is important to guide treatment and to retrospectively elucidate the effects of therapy …
rhythms is important to guide treatment and to retrospectively elucidate the effects of therapy …
[HTML][HTML] Patient's airway monitoring during cardiopulmonary resuscitation using deep networks
M Marhamati, B Dorry, S Imannezhad… - Medical Engineering & …, 2024 - Elsevier
Cardiopulmonary resuscitation (CPR) is a crucial life-saving technique commonly
administered to individuals experiencing cardiac arrest. Among the important aspects of …
administered to individuals experiencing cardiac arrest. Among the important aspects of …
A machine learning model for the prognosis of pulseless electrical activity during out-of-hospital cardiac arrest
Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical
and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of …
and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of …
A super SDM (species distribution model)'in the cloud'for better habitat-association inference with a 'big data'application of the Great Gray Owl for Alaska
The currently available distribution and range maps for the Great Grey Owl (GGOW; Strix
nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus …
nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus …
Automatic detection of ventilations during mechanical cardiopulmonary resuscitation
Feedback on chest compressions and ventilations during cardiopulmonary resuscitation
(CPR) is important to improve survival from out-of-hospital cardiac arrest (OHCA). The …
(CPR) is important to improve survival from out-of-hospital cardiac arrest (OHCA). The …