Exploring artificial intelligence algorithms for electrocardiogram (ECG) signal analysis: A comprehensive review

MF Safdar, RM Nowak, P Pałka - Computers in Biology and Medicine, 2023 - Elsevier
Electrocardiogram (ECG) are the physiological signals and a standard test to measure the
heart's electrical activity that depicts the movement of cardiac muscles. A review study has …

[HTML][HTML] Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review

J Toy, N Bosson, S Schlesinger, M Gausche-Hill… - Resuscitation …, 2023 - Elsevier
Background Artificial intelligence (AI) has demonstrated significant potential in supporting
emergency medical services personnel during out-of-hospital cardiac arrest (OHCA) care; …

Transfer learning based deep network for signal restoration and rhythm analysis during cardiopulmonary resuscitation using only the ECG waveform

Y Gong, L Wei, S Yan, F Zuo, H Zhang, Y Li - Information Sciences, 2023 - Elsevier
Minimizing the interruption of cardiopulmonary resuscitation (CPR) is an important
technique to improve the survival of out-of-hospital cardiac arrest (OHCA) patients. Recent …

Hybrid lightweight Deep-learning model for Sensor-fusion basketball Shooting-posture recognition

J Fan, S Bi, R Xu, L Wang, L Zhang - Measurement, 2022 - Elsevier
Shooting-posture recognition is an important area in basketball technical movement
recognition domain. This paper proposes the squeeze convolutional gated attention (SCGA) …

[HTML][HTML] Language function following preterm birth: prediction using machine learning

E Valavani, M Blesa, P Galdi, G Sullivan, B Dean… - Pediatric …, 2022 - nature.com
Background Preterm birth can lead to impaired language development. This study aimed to
predict language outcomes at 2 years corrected gestational age (CGA) for children born …

[PDF][PDF] RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis

SH Wang, Z Zhu, YD Zhang - Frontiers in public health, 2021 - frontiersin.org
Objective: COVID-19 is a sort of infectious disease caused by a new strain of coronavirus.
This study aims to develop a more accurate COVID-19 diagnosis system. Methods: First, the …

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 …

[HTML][HTML] Real-time amplitude spectrum area estimation during chest compression from the ECG waveform using a 1D convolutional neural network

F Zuo, C Dai, L Wei, Y Gong, C Yin, Y Li - Frontiers in Physiology, 2023 - frontiersin.org
Introduction: Amplitude spectrum area (AMSA) is a well-established measure than can
predict defibrillation outcome and guiding individualized resuscitation of ventricular …

The ability of machine learning algorithms to predict defibrillation success during cardiac arrest: A systematic review

M Sem, E Mastrangelo, D Lightfoot, T Aves, S Lin… - Resuscitation, 2023 - Elsevier
Objective To evaluate the existing knowledge on the effectiveness of machine learning (ML)
algorithms in predicting defibrillation success during in-and out-of-hospital cardiac arrest …

Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review.

N Bosson, S Schlesinger, M Gausche-Hill, S Stratton… - 2023 - escholarship.org
BACKGROUND: Artificial intelligence (AI) has demonstrated significant potential in
supporting emergency medical services personnel during out-of-hospital cardiac arrest …