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Uncertainty

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Detecting slender objects with uncertainty based on keypoint-displacement representation.

Neural networks : the official journal of the International Neural Network Society
Slender objects are long and thin objects. Existing object detection networks are not specially designed for detecting slender objects. We propose a method to detect slender objects. We represent slender objects with a keypoint-displacement pattern i...

Computation of epistemic uncertainty due to limited data samples in small field dosimetry using Fuzzy Set Theory.

The British journal of radiology
OBJECTIVE: To estimate the epistemic (or fuzzy) uncertainty, arising due to limited data samples in the measurement of the output factors (OFs) of the small fields using Fuzzy Set Theory (FST).

Uncertainty Quantification and Sensitivity Analysis of Partial Charges on Macroscopic Solvent Properties in Molecular Dynamics Simulations with a Machine Learning Model.

Journal of chemical information and modeling
The molecular dynamics (MD) simulation technique is among the most broadly used computational methods to investigate atomistic phenomena in a variety of chemical and biological systems. One of the most common (and most uncertain) parametrization step...

Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Physics in medicine and biology
Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its image quality is degraded due to noise and scatter. Although several correction methods have been propos...

Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice.

PLoS computational biology
We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; ...

StoCast: Stochastic Disease Forecasting With Progression Uncertainty.

IEEE journal of biomedical and health informatics
Forecasting patients' disease progressions with rich longitudinal clinical data has drawn much attention in recent years due to its impactful application in healthcare and the medical field. Researchers have tackled this problem by leveraging traditi...

Synchronization criteria of delayed inertial neural networks with generally Markovian jumping.

Neural networks : the official journal of the International Neural Network Society
In this paper, the synchronization problem of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. The second order differential equations are transformed into the first-order differential equations by ut...

A comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks.

Physics in medicine and biology
Recently, artificial intelligence technologies and algorithms have become a major focus for advancements in treatment planning for radiation therapy. As these are starting to become incorporated into the clinical workflow, a major concern from clinic...

A generative adversarial network approach to (ensemble) weather prediction.

Neural networks : the official journal of the International Neural Network Society
We use a conditional deep convolutional generative adversarial network to predict the geopotential height of the 500 hPa pressure level, the two-meter temperature and the total precipitation for the next 24 h over Europe. The proposed models are trai...

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Scientific reports
Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and i...