A review on bayesian deep learning in healthcare: Applications and challenges

AA Abdullah, MM Hassan, YT Mustafa - IEEe Access, 2022‏ - ieeexplore.ieee.org
In the last decade, Deep Learning (DL) has revolutionized the use of artificial intelligence,
and it has been deployed in different fields of healthcare applications such as image …

Uncertainty quantification in DenseNet model using myocardial infarction ECG signals

V Jahmunah, EYK Ng, RS Tan, SL Oh… - Computer Methods and …, 2023‏ - Elsevier
Background and objective Myocardial infarction (MI) is a life-threatening condition
diagnosed acutely on the electrocardiogram (ECG). Several errors, such as noise, can …

[HTML][HTML] Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram

M Barandas, L Famiglini, A Campagner, D Folgado… - Information …, 2024‏ - Elsevier
Artificial Intelligence (AI) use in automated Electrocardiogram (ECG) classification has
continuously attracted the research community's interest, motivated by their promising …

Uncertainty Quantification in Machine Learning for Biosignal Applications--A Review

IP de Jong, AI Sburlea, M Valdenegro-Toro - arxiv preprint arxiv …, 2023‏ - arxiv.org
Uncertainty Quantification (UQ) has gained traction in an attempt to fix the black-box nature
of Deep Learning. Specifically (medical) biosignals such as electroencephalography (EEG) …

Enhancing Electrocardiography Data Classification Confidence: A Robust Gaussian Process Approach (MuyGPs)

UV Nnyaba, HM Shemtaga, DW Collins… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Analyzing electrocardiography (ECG) data is essential for diagnosing and monitoring
various heart diseases. The clinical adoption of automated methods requires accurate …

Effect of dimensionality reduction on uncertainty quantification in trustworthy machine learning

YC Li, J Zhan - … on Machine Learning and Cybernetics (ICMLC), 2023‏ - ieeexplore.ieee.org
Machine learning (ML) is a commonly employed computer-assisted tool for ECG diagnosis
with above 85% correct. However, the interpretability of the prediction has become a barrier …

Deciphering Heartbeat Signatures: A Vision Transformer Approach to Explainable Atrial Fibrillation Detection from ECG Signals

A Mohan, D Elbers, O Zilbershot… - 2024 46th Annual …, 2024‏ - ieeexplore.ieee.org
Remote patient monitoring based on wearable single-lead electrocardiogram (ECG) devices
has significant potential for enabling the early detection of heart disease, especially in …

AI-Driven Atrial Arrhythmia Detection: Development, Cross-Comparison and Uncertainty Quantification of Algorithms for Clinical Continuous ECGs

MM Rahman - 2024‏ - air.unimi.it
Background: Atrial arrhythmias, particularly atrial fibrillation (AF), are prevalent
cardiovascular disorders characterized by irregular heart rhythms originating from the atria …

[PDF][PDF] Variational Auto-Encoder for Latent Uncertainty Encoding in Large Language Models

S Paun - 2025‏ - essay.utwente.nl
Uncertainty is both a phenomenon that is an integral part of the human experience and a
fundamental concept that spans a multitude of disciplines, including psychology, cognitive …

Uncertainty in Machine Learning a Safety Perspective on Biomedical Applications

MSG Barandas - 2023‏ - search.proquest.com
Uncertainty is an inevitable and essential aspect of the worldwe live in and a fundamental
aspect of human decision-making. It is no different in the realm of machine learning. Just as …