AIMC Topic: Uncertainty

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Unsupervised Domain Adaptation for Low-Dose CT Reconstruction via Bayesian Uncertainty Alignment.

IEEE transactions on neural networks and learning systems May 2, 2025
Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning (DL) is widely used in this problem, but the performance of testing data (also known...
Radiation Dosage Uncertainty Image Processing, Computer-Assisted Unsupervised Machine Learning Bayes Theorem Tomography, X-Ray Computed Deep Learning Humans Algorithms
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Structural uncertainty estimation for medical image segmentation.

Medical image analysis Apr 28, 2025
Precise segmentation and uncertainty estimation are crucial for error identification and correction in medical diagnostic assistance. Existing methods mainly rely on pixel-wise uncertainty estimations. They (1) neglect the global context, leading to ...
Image Interpretation, Computer-Assisted Uncertainty Ultrasonography Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Reproducibility of Results
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CUAMT: A MRI semi-supervised medical image segmentation framework based on contextual information and mixed uncertainty.

Computer methods and programs in biomedicine Apr 27, 2025
BACKGROUND AND OBJECTIVE: Semi-supervised medical image segmentation is a class of machine learning paradigms for segmentation model training and inference using both labeled and unlabeled medical images, which can effectively reduce the data labelin...
Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Uncertainty Machine Learning Algorithms Brain Neoplasms
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Multi-Granularity Autoformer for long-term deterministic and probabilistic power load forecasting.

Neural networks : the official journal of the International Neural Network Society Apr 24, 2025
Long-term power load forecasting is critical for power system planning but is constrained by intricate temporal patterns. Transformer-based models emphasize modeling long- and short-term dependencies yet encounter limitations from complexity and para...
Humans Probability Electric Power Supplies Uncertainty Neural Networks, Computer Forecasting Models, Statistical
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ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiography.

Medical image analysis Apr 24, 2025
Aortic stenosis (AS) is a prevalent heart valve disease that requires accurate and timely diagnosis for effective treatment. Current methods for automated AS severity classification rely on black-box deep learning techniques, which suffer from a low ...
Humans Neural Networks, Computer Echocardiography Severity of Illness Index Image Interpretation, Computer-Assisted Deep Learning Aortic Valve Stenosis Uncertainty
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Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes.

Medical image analysis Apr 20, 2025
Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI frame...
Uncertainty Diffusion Magnetic Resonance Imaging Monte Carlo Method White Matter Diffusion Tensor Imaging Markov Chains Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Brain Computer Simulation Reproducibility of Results Bayes Theorem Humans
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Effect of Uncertainty-Aware AI Models on Pharmacists' Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial.

JMIR medical informatics Apr 18, 2025
BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems are increasingly used in health care. Uncertainty-aware AI presents the model's confidence in its decision alongside its prediction, whereas black-box AI only provides a...
Uncertainty Middle Aged Female Pharmacists Internet Adult Humans Decision Support Systems, Clinical Male Reaction Time Artificial Intelligence Decision Making Cross-Over Studies
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Uncertainty-aware segmentation quality prediction via deep learning Bayesian Modeling: Comprehensive evaluation and interpretation on skin cancer and liver segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 13, 2025
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. However, in clinical settings without manual annotations, assessing segmenta...
Reproducibility of Results Uncertainty Humans Skin Neoplasms Deep Learning Liver Neoplasms Image Processing, Computer-Assisted Bayes Theorem Image Interpretation, Computer-Assisted
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Evaluating medical AI systems in dermatology under uncertain ground truth.

Medical image analysis Apr 9, 2025
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However, in medical applications, this ground truth is often curated in the f...
Humans Dermatology Artificial Intelligence Uncertainty Algorithms Diagnosis, Differential Skin Diseases
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Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.

Oncotarget Apr 4, 2025
Recent advances in deep learning models have transformed medical imaging analysis, particularly in radiology. This editorial outlines how uncertainty quantification through embedding-based approaches enhances diagnostic accuracy and reliability in he...
Uncertainty Liver Neoplasms Diagnostic Imaging Quality Assurance, Health Care Humans Reproducibility of Results Deep Learning
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