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A review on bayesian deep learning in healthcare: Applications and challenges
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 …
and it has been deployed in different fields of healthcare applications such as image …
Uncertainty quantification in DenseNet model using myocardial infarction ECG signals
Background and objective Myocardial infarction (MI) is a life-threatening condition
diagnosed acutely on the electrocardiogram (ECG). Several errors, such as noise, can …
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
Artificial Intelligence (AI) use in automated Electrocardiogram (ECG) classification has
continuously attracted the research community's interest, motivated by their promising …
continuously attracted the research community's interest, motivated by their promising …
Uncertainty Quantification in Machine Learning for Biosignal Applications--A Review
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) …
of Deep Learning. Specifically (medical) biosignals such as electroencephalography (EEG) …
Enhancing Electrocardiography Data Classification Confidence: A Robust Gaussian Process Approach (MuyGPs)
Analyzing electrocardiography (ECG) data is essential for diagnosing and monitoring
various heart diseases. The clinical adoption of automated methods requires accurate …
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 …
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
Remote patient monitoring based on wearable single-lead electrocardiogram (ECG) devices
has significant potential for enabling the early detection of heart disease, especially in …
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 …
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 …
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 …
aspect of human decision-making. It is no different in the realm of machine learning. Just as …