AIMC Topic: Uncertainty

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Sustainability prioritization of sewage sludge to energy scenarios with hybrid-data consideration: a fuzzy decision-making framework based on full consistency method and fusion ranking model.

Environmental science and pollution research international Sep 24, 2020
This work proposed a novel mathematical framework for the sustainability assessment of sewage sludge to energy (SStE) scenarios, by resorting to fuzzy multi-criteria decision-making (MCMD) methods. In which, an evaluation system including twelve crit...
Sewage Uncertainty Fuzzy Logic Decision Making
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Boundary Mittag-Leffler stabilization of fractional reaction-diffusion cellular neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 15, 2020
Mittag-Leffler stabilization is studied for fractional reaction-diffusion cellular neural networks (FRDCNNs) in this paper. Different from previous literature, the FRDCNNs in this paper are high-dimensional systems, and boundary control and observed-...
Uncertainty Neural Networks, Computer Diffusion
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A machine learning framework with anatomical prior for online dose verification using positron emitters and PET in proton therapy.

Physics in medicine and biology Sep 14, 2020
We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information o...
Electrons Positron-Emission Tomography Machine Learning Image Processing, Computer-Assisted Radiotherapy Dosage Proton Therapy Uncertainty Radiation Dosage Signal-To-Noise Ratio Humans Neural Networks, Computer
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Fetal brain age estimation and anomaly detection using attention-based deep ensembles with uncertainty.

NeuroImage Sep 2, 2020
MRI-based brain age prediction has been widely used to characterize normal brain development, and deviations from the typical developmental trajectory are indications of brain abnormalities. Age prediction of the fetal brain remains unexplored, altho...
Humans Neural Networks, Computer Prenatal Diagnosis Fetal Development Uncertainty Magnetic Resonance Imaging Gestational Age Brain Image Processing, Computer-Assisted
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Improving depth-of-interaction resolution in pixellated PET detectors using neural networks.

Physics in medicine and biology Aug 27, 2020
Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation positio...
Positron-Emission Tomography Linear Models Calibration Uncertainty Neural Networks, Computer Image Processing, Computer-Assisted Humans
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Automated quantification of myocardial tissue characteristics from native T mapping using neural networks with uncertainty-based quality-control.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Aug 20, 2020
BACKGROUND: Tissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Nat...
Myocardium Reproducibility of Results Quality Control Uncertainty Humans Image Interpretation, Computer-Assisted Automation Predictive Value of Tests Case-Control Studies Ventricular Function, Left Neural Networks, Computer Cardiomyopathies Stroke Volume Magnetic Resonance Imaging Bayes Theorem
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Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.

Journal of digital imaging Aug 19, 2020
The ideal radiology report reduces diagnostic uncertainty, while avoiding ambiguity whenever possible. The purpose of this study was to characterize the use of uncertainty terms in radiology reports at a single institution and compare the use of thes...
Research Report Radiology Information Systems Uncertainty Natural Language Processing Radiology Humans
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Uncertainty Quantification Using Neural Networks for Molecular Property Prediction.

Journal of chemical information and modeling Aug 4, 2020
Uncertainty quantification (UQ) is an important component of molecular property prediction, particularly for drug discovery applications where model predictions direct experimental design and where unanticipated imprecision wastes valuable time and r...
Uncertainty Neural Networks, Computer Drug Discovery
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Left ventricle quantification with sample-level confidence estimation via Bayesian neural network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 26, 2020
Quantification of cardiac left ventricle has become a hot topic due to its great significance in clinical practice. Many efforts have been devoted to LV quantification and obtained promising performance with the help of various deep neural networks w...
Heart Ventricles Humans Uncertainty Neural Networks, Computer Bayes Theorem
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Integrating uncertainty in deep neural networks for MRI based stroke analysis.

Medical image analysis Jul 19, 2020
At present, the majority of the proposed Deep Learning (DL) methods provide point predictions without quantifying the model's uncertainty. However, a quantification of the reliability of automated image analysis is essential, in particular in medicin...
Bayes Theorem Reproducibility of Results Uncertainty Stroke Humans Magnetic Resonance Imaging Neural Networks, Computer
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