AIMC Topic: Electrocardiography
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Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.
Scientific reports
Jul 31, 2025
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...
Classifying social and physical pain from multimodal physiological signals using machine learning.
Scientific reports
Jul 29, 2025
Accurate pain assessment is essential for effective management; however, most studies have focused on differentiating pain from non-pain or estimating pain intensity rather than distinguishing between distinct pain types. We present a machine learnin...
Identifying key physiological and clinical factors for traumatic brain injury patient management using network analysis and machine learning.
PloS one
Jul 28, 2025
In the intensive care unit (ICU), managing traumatic brain injury (TBI) patients presents significant challenges due to the dynamic interaction between physiological and clinical markers. This study aims to uncover these subtle interconnections and i...
Evaluating GPT-4's role in critical patient management in emergency departments.
PloS one
Jul 24, 2025
INTRODUCTION: Recent advancements in artificial intelligence (AI) have introduced tools like ChatGPT-4, capable of interpreting visual data, including ECGs. In our study,we aimed to investigate the effectiveness of GPT-4 in interpreting ECGs and mana...
Electrocardiographic sex index: a continuous representation of sex.
Biology of sex differences
Jul 17, 2025
Clinical risk calculators consider sex as a binary variable. However, sex is a complex trait with anatomic, physiologic, and metabolic attributes that are not easily summarized in this manner [1]. We propose a continuous representation of sex, the EC...
ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.
Physiological measurement
Jul 11, 2025
. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate and efficient detection methods.. This study proposes ModelS4Apnea, a deep learning framework for sleep apnea detection from electrocardiogram (ECG) ...
Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.
PloS one
Jul 11, 2025
This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Personalized Models and Differential Privacy (FLPMDP), for diagnosing arrhythmia from 12-lead electrocardiogram (ECG) signals. The architecture supports ...
Evolving Blood Pressure Estimation: From Feature Analysis to Image-Based Deep Learning Models.
Journal of medical systems
Jul 9, 2025
Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological signals, such as electrocardiogram (ECG) and photoplethysmography (PPG), from two distinct body sites to compute metrics like pulse transit time (PTT) ...
Efficient pretraining of ECG scalogram images using masked autoencoders for cardiovascular disease diagnosis.
Scientific reports
Jul 8, 2025
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, emphasizing the need for accurate and early diagnosis. Electrocardiograms (ECG) provide a non-invasive means of diagnosing various cardiac conditions. However, traditional m...
Filter-type neural network-based counter-pulsation control in pulsatile ECMO: improving heartbeat-pulse discrimination and synchronization accuracy.
Biomedical engineering online
Jul 7, 2025
Implementing counter-pulsation (CP) control in pulsatile extracorporeal membrane oxygenator (p-ECMO) systems offers a refined approach to mitigate risks commonly associated with conventional ECMOs. To attain CP between the p-ECMO and heart, accurate ...
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