AIMC Topic: Uncertainty
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Weakly supervised nuclei segmentation based on pseudo label correction and uncertainty denoising.
Artificial intelligence in medicine
Jun 1, 2025
Nuclei segmentation plays a vital role in computer-aided histopathology image analysis. Numerous fully supervised learning approaches exhibit amazing performance relying on pathological image with precisely annotations. Whereas, it is difficult and t...
Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification.
Nature communications
May 30, 2025
The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is acknowledged as the optimal modality for live-cell su...
Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CT.
Physics in medicine and biology
May 23, 2025
Deep learning models are increasingly being implemented for automated medical image analysis to inform patient care. Most models, however, lack uncertainty information, without which the reliability of model outputs cannot be ensured. Several uncerta...
FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17.
Scientific reports
May 21, 2025
Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging te...
Patient-specific uncertainty calibration of deep learning-based autosegmentation networks for adaptive MRI-guided lung radiotherapy.
Physics in medicine and biology
May 16, 2025
Uncertainty assessment of deep learning autosegmentation (DLAS) models can support contour corrections in adaptive radiotherapy (ART), e.g. by utilizing Monte Carlo Dropout (MCD) uncertainty maps. However, poorly calibrated uncertainties at the patie...
Knowledge Uncertainty Estimation for Reliable Clinical Decision Support: A Delirium Risk Prognosis Case Study.
Studies in health technology and informatics
Apr 24, 2025
INTRODUCTION: Predictive models hold significant potential in healthcare, but their adoption in clinical settings is hampered by limited trust due to their inability to recognize when presented with unfamiliar data. Estimating knowledge uncertainty (...
Unraveling Uncertainty: The Impact of Biological and Analytical Variation on the Prediction Uncertainty of Categorical Prediction Models.
The journal of applied laboratory medicine
Mar 3, 2025
BACKGROUND: Interest in prediction models, including machine learning (ML) models, based on laboratory data has increased tremendously. Uncertainty in laboratory measurements and predictions based on such data are inherently intertwined. This study d...
Uncertainty CNNs: A path to enhanced medical image classification performance.
Mathematical biosciences and engineering : MBE
Feb 20, 2025
The automated detection of tumors using medical imaging data has garnered significant attention over the past decade due to the critical need for early and accurate diagnoses. This interest is fueled by advancements in computationally efficient model...
A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes.
Journal of vision
Feb 3, 2025
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...
Complex nth power root fuzzy sets: Theory, and applications for multi-attribute decision making in uncertain environments.
PloS one
Jan 1, 2025
The newly introduced nth power root fuzzy set is a useful tool for expressing ambiguity and vagueness. It has an improved ability to manage uncertain situations compared to intuitionistic fuzzy set and Pythagorean fuzzy set theories, making nth power...
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