Transformers in biosignal analysis: A review

A Anwar, Y Khalifa, JL Coyle, E Sejdic - Information Fusion, 2024 - Elsevier
Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …

Improving deep-learning electrocardiogram classification with an effective coloring method

WW Chen, CC Tseng, CC Huang, HHS Lu - Artificial intelligence in …, 2024 - Elsevier
Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality
worldwide. Electrocardiogram (ECG) analysis plays a pivotal role in cardiovascular disease …

2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low-and Middle …

P Lu, AP Creagh, HY Lu, HB Hai, VITAL Consortium… - Sensors, 2023 - mdpi.com
Tetanus is a life-threatening bacterial infection that is often prevalent in low-and middle-
income countries (LMIC), Vietnam included. Tetanus affects the nervous system, leading to …

Continuous patient state attention model for addressing irregularity in electronic health records

VK Chauhan, A Thakur, O O'Donoghue… - BMC Medical Informatics …, 2024 - Springer
Background Irregular time series (ITS) are common in healthcare as patient data is recorded
in an electronic health record (EHR) system as per clinical guidelines/requirements but not …

Identification of congenital valvular murmurs in young patients using deep learning-based attention transformers and phonocardiograms

M Alkhodari, LJ Hadjileontiadis… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
One in every four newborns suffers from congenital heart disease (CHD) that causes defects
in the heart structure. The current gold-standard assessment technique, echocardiography …

A Small-Scale Switch Transformer and NLP-based Model for Clinical Narratives Classification

TD Le, P Jouvet, R Noumeir - arXiv preprint arXiv:2303.12892, 2023 - arxiv.org
In recent years, Transformer-based models such as the Switch Transformer have achieved
remarkable results in natural language processing tasks. However, these models are often …

Abnormal recognition-assisted and onset-offset aware network for pathological wearable ECG delineation

Y Zhang, J Lai, C Zhao, J Wang, Y Yan, M Chen… - Artificial Intelligence in …, 2024 - Elsevier
Electrocardiogram (ECG) delineation is essential to the identification of abnormal cardiac
status, especially when ECG signals are remotely monitored with wearable devices. The …

Continuous patient state attention models

VK Chauhan, A Thakur, O O'Donoghue, O Rohanian… - Medrxiv, 2022 - medrxiv.org
Irregular time-series (ITS) are prevalent in the electronic health records (EHR) as the data is
recorded in EHR system as per the clinical guidelines/requirements but not for research and …

Systemic immune inflammation index as a predictor of disease severity in tetanus patients: A retrospective observational study

D Cheng, D Wenying, H Jizheng, S Wei, L Liang… - PloS one, 2024 - journals.plos.org
Objective This study aimed to analyze the predictive value of the systemic immune
inflammation index (SII) for the severity of disease in tetanus patients. Methods Clinical data …

Advancing ECG Biometrics Through Vision Transformers: A Confidence-Driven Approach

O D'angelis, L Bacco, L Vollero, M Merone - IEEE Access, 2023 - ieeexplore.ieee.org
Over the past two decades, Electrocardiography (ECG) has gained significant momentum in
the field of biometrics, offering a compelling alternative for person identity recognition based …