AIMC Topic: Uncertainty

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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 Mar 17, 2021
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...
Solvents Static Electricity Uncertainty Machine Learning Molecular Dynamics Simulation
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Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Physics in medicine and biology Mar 16, 2021
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...
Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans Protons Bayes Theorem Monte Carlo Method Proton Therapy Image Processing, Computer-Assisted Head Phantoms, Imaging Head and Neck Neoplasms Uncertainty Calibration Reproducibility of Results Deep Learning
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Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice.

PLoS computational biology Mar 11, 2021
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; ...
Models, Neurological Decision Making Brain Computational Biology Uncertainty Humans Neural Networks, Computer
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StoCast: Stochastic Disease Forecasting With Progression Uncertainty.

IEEE journal of biomedical and health informatics Mar 5, 2021
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...
Humans Forecasting Alzheimer Disease Neural Networks, Computer Uncertainty Machine Learning
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Synchronization criteria of delayed inertial neural networks with generally Markovian jumping.

Neural networks : the official journal of the International Neural Network Society Feb 24, 2021
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...
Uncertainty Neural Networks, Computer Algorithms Markov Chains Time Factors Pattern Recognition, Automated
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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 Feb 24, 2021
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...
Humans Deep Learning Uncertainty Radiotherapy Dosage Monte Carlo Method Radiotherapy Planning, Computer-Assisted Radiation Dosage
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A generative adversarial network approach to (ensemble) weather prediction.

Neural networks : the official journal of the International Neural Network Society Feb 21, 2021
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...
Forecasting Deep Learning Uncertainty Neural Networks, Computer Weather Monte Carlo Method
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Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Scientific reports Feb 16, 2021
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...
Patient-Specific Modeling Imaging Genomics Genes, erbB-1 Gene Amplification Uncertainty Magnetic Resonance Imaging Glioblastoma Humans Machine Learning
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Adaptive Neural Control for a Class of Nonlinear Multiagent Systems.

IEEE transactions on neural networks and learning systems Feb 4, 2021
This article studies the adaptive neural controller design for a class of uncertain multiagent systems described by ordinary differential equations (ODEs) and beams. Three kinds of agent models are considered in this study, i.e., beams, nonlinear ODE...
Brain-Computer Interfaces Uncertainty Neural Networks, Computer Feedback Nonlinear Dynamics Algorithms
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A dynamic generalized fuzzy multi-criteria croup decision making approach for green supplier segmentation.

PloS one Jan 25, 2021
Supplier selection and segmentation are crucial tasks of companies in order to reduce costs and increase the competitiveness of their goods. To handle uncertainty and dynamicity in the supplier segmentation problem, this research thus proposes a new ...
Models, Theoretical Decision Making Fuzzy Logic Uncertainty
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