AIMC Topic: Uncertainty
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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-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...
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...
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...
CTUSurv: A Cell-Aware Transformer-Based Network With Uncertainty for Survival Prediction Using Whole Slide Images.
IEEE transactions on medical imaging
Apr 3, 2025
Image-based survival prediction through deep learning techniques represents a burgeoning frontier aimed at augmenting the diagnostic capabilities of pathologists. However, directly applying existing deep learning models to survival prediction may not...
Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.
Medical physics
Apr 1, 2025
BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown rapidly, thus making available a large volume of organ dose information. With modern c...
Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.
NeuroImage
Apr 1, 2025
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...
A Framework for Parameter Estimation and Uncertainty Quantification in Systems Biology Using Quantile Regression and Physics-Informed Neural Networks.
Bulletin of mathematical biology
Mar 28, 2025
A framework for parameter estimation and uncertainty quantification is crucial for understanding the mechanisms of biological interactions within complex systems and exploring their dynamic behaviors beyond what can be experimentally observed. Despit...
Artefacts of Change: The Disruptive Nature of Humanoid Robots Beyond Classificatory Concerns.
Science and engineering ethics
Mar 28, 2025
One characteristic of socially disruptive technologies is that they have the potential to cause uncertainty about the application conditions of a concept i.e., they are conceptually disruptive. Humanoid robots have done just this, as evidenced by dis...
Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 25, 2025
PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure level is essential for clinical introduction. In a previous study, a DL model was developed for oropharyngeal cancer (OPC) primary tumor (PT) segmentati...
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