Build a bridge between ECG and EEG signals for atrial fibrillation diagnosis using AI methods

M Li, X Zeng, F Wu, Y Chu, W Wei, M Fan… - Computers in Biology …, 2023 - Elsevier
Atrial fibrillation (AF) is a very common type of cardiac arrhythmia. The main characteristic of
AF is an abnormally rapid and disordered atrial rhythm causing an atrial dysfunction, which …

Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review

K Glaser, L Marino, JD Stubnya, F Bilotta - Journal of Anesthesia, 2024 - Springer
Atrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients.
Nevertheless, the absence of a swift and precise method for prediction and detection poses …

The ESICM datathon and the ESICM and ICMx data science strategy

P Elbers, P Thoral, LDJ Bos, M Greco… - Intensive Care Medicine …, 2024 - Springer
In this issue of Intensive Care Medicine Experimental we celebrate the success of the
ESICM datathons. The fifth consecutive edition was held in the months of May and June …

Real-time Patient Response Forecasting in ICU: A Robust Model Driven by LSTM and Advanced Data Processing Approaches

T Kumaragurubaran, VR SR… - 2024 2nd International …, 2024 - ieeexplore.ieee.org
People who are in an ICU (intensive care unit) are especially vulnerable to the adverse
consequences of drugs, especially infusion drugs, because the rate and dose of the …

Predictive Modelling of Critical Vital Signs in ICU Patients by Machine Learning: An Early Warning System for Improved Patient Outcomes

T Kumaragurubaran, VR SR… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
Accurate monitoring of vital signs in an ICU is integral to understanding overall physical well-
being for patients. Our research endeavor employed machine learning techniques to …

[引用][C] Atrial fibrillation in critical care

D Lancini - 2024 - espace.library.uq.edu.au
Atrial fibrillation (AF) has been widely investigated in the ambulatory setting, with an
extensive volume of published data to inform current understanding of its pathophysiology …