AIMC Topic: Uncertainty

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Federated learning meets Bayesian neural network: Robust and uncertainty-aware distributed variational inference.

Neural networks : the official journal of the International Neural Network Society Jan 13, 2025
Federated Learning (FL) is a popular framework for data privacy protection in distributed machine learning. However, current FL faces some several problems and challenges, including the limited amount of client data and data heterogeneity. These lead...
Federated Learning Bayes Theorem Uncertainty Humans Neural Networks, Computer Machine Learning Algorithms
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Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.

Scientific reports Jan 8, 2025
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it cha...
Humans Diabetic Retinopathy Neural Networks, Computer Bayes Theorem Uncertainty Deep Learning Image Processing, Computer-Assisted
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Uncertainty Global Contrastive Learning Framework for Semi-Supervised Medical Image Segmentation.

IEEE journal of biomedical and health informatics Jan 7, 2025
In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different segmented objects, classifying segmentation boundaries becomes chall...
Algorithms Databases, Factual Image Processing, Computer-Assisted Humans Supervised Machine Learning Image Interpretation, Computer-Assisted Uncertainty Fuzzy Logic Diagnostic Imaging
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Uncertainty modeling for inductive knowledge graph embedding.

Neural networks : the official journal of the International Neural Network Society Jan 6, 2025
In the process of refining Knowledge Graphs (KGs), new entities emerge, and old entities evolve, which usually updates their attribute information and neighborhood structures. This results in a distribution shift problem for entity features in the em...
Machine Learning Humans Algorithms Neural Networks, Computer Normal Distribution Uncertainty
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DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 4, 2025
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to q...
Uncertainty Diffusion Magnetic Resonance Imaging Deep Learning Brain Diseases Humans Ensemble Learning Brain Neural Networks, Computer Adult
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AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model.

Acta psychologica Jan 3, 2025
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated ...
Saudi Arabia Motivation Uncertainty Artificial Intelligence Male Humans Female Writing Students Young Adult Learning Adult
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Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images.

Scientific reports Jan 2, 2025
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addre...
ROC Curve Image Processing, Computer-Assisted Muscle, Skeletal Middle Aged Deep Learning Hip Uncertainty Humans Tomography, X-Ray Computed Female Aged Male
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Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging.

IEEE transactions on medical imaging Jan 2, 2025
Data uncertainties, such as sensor noise, occlusions or limitations in the acquisition method can introduce irreducible ambiguities in images, which result in varying, yet plausible, semantic hypotheses. In Machine Learning, this ambiguity is commonl...
Uncertainty Models, Statistical Humans Diagnostic Imaging Machine Learning Algorithms Brain Image Processing, Computer-Assisted
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A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images With Multi-Relationship Graph Learning.

IEEE transactions on medical imaging Jan 2, 2025
Chest radiography, commonly known as CXR, is frequently utilized in clinical settings to detect cardiopulmonary conditions. However, even seasoned radiologists might offer different evaluations regarding the seriousness and uncertainty associated wit...
Benchmarking Humans Lung Radiography, Thoracic Databases, Factual Deep Learning Uncertainty Radiographic Image Interpretation, Computer-Assisted
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Unveiling pathology-related predictive uncertainty of glomerular lesion recognition using prototype learning.

Journal of biomedical informatics Dec 31, 2024
OBJECTIVE: Recognizing glomerular lesions is essential in diagnosing chronic kidney disease. However, deep learning faces challenges due to the lesion heterogeneity, superposition, progression, and tissue incompleteness, leading to uncertainty in mod...
Uncertainty Deep Learning Humans Renal Insufficiency, Chronic Algorithms Kidney Glomerulus
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