AIMC Topic: Uncertainty

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Can uncertainty estimation predict segmentation performance in ultrasound bone imaging?

International journal of computer assisted radiology and surgery Apr 4, 2022
PURPOSE: Segmenting bone surfaces in ultrasound (US) is a fundamental step in US-based computer-assisted orthopaedic surgeries. Neural network-based segmentation techniques are a natural choice for this, given promising results in related tasks. Howe...
Diagnostic Imaging Uncertainty Image Processing, Computer-Assisted Humans Ultrasonography Neural Networks, Computer
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Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images.

IEEE transactions on medical imaging Apr 1, 2022
Despite the promise of Convolutional neural network (CNN) based classification models for histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may suffer from overfitting when the data is biased. We show that Bayes...
Breast Uncertainty Bayes Theorem Neural Networks, Computer
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A Novel Prescribed-Performance-Tracking Control System with Finite-Time Convergence Stability for Uncertain Robotic Manipulators.

Sensors (Basel, Switzerland) Mar 29, 2022
Through this article, we present an advanced prescribed performance-tracking control system with finite-time convergence stability for uncertain robotic manipulators. It is therefore necessary to define a suitable performance function and error trans...
Computer Simulation Robotics Algorithms Uncertainty Robotic Surgical Procedures
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Bayesian deep learning-based H-MRS of the brain: Metabolite quantification with uncertainty estimation using Monte Carlo dropout.

Magnetic resonance in medicine Mar 28, 2022
PURPOSE: To develop a Bayesian convolutional neural network (BCNN) with Monte Carlo dropout sampling for metabolite quantification with simultaneous uncertainty estimation in deep learning-based proton MRS of the brain.
Uncertainty Monte Carlo Method Humans Brain Macromolecular Substances Deep Learning Bayes Theorem
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Research and Forecast Analysis of Financial Stability for Policy Uncertainty.

Computational intelligence and neuroscience Mar 24, 2022
The instability of financial market will have a great impact on money, bonds, and stocks and affect the economic development of society and people's lives. Therefore, it is very necessary for us to study and predict the financial stability. According...
Neural Networks, Computer Forecasting Algorithms Uncertainty Humans Policy
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Method to Minimize the Errors of AI: Quantifying and Exploiting Uncertainty of Deep Learning in Brain Tumor Segmentation.

Sensors (Basel, Switzerland) Mar 21, 2022
Despite the unprecedented success of deep learning in various fields, it has been recognized that clinical diagnosis requires extra caution when applying recent deep learning techniques because false prediction can result in severe consequences. In t...
Brain Neoplasms Humans Radiography Uncertainty Deep Learning
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Quantifying uncertainty in machine learning classifiers for medical imaging.

International journal of computer assisted radiology and surgery Mar 12, 2022
PURPOSE: Machine learning (ML) models in medical imaging (MI) can be of great value in computer aided diagnostic systems, but little attention is given to the confidence (alternatively, uncertainty) of such models, which may have significant clinical...
Uncertainty Diagnostic Imaging Neural Networks, Computer Reproducibility of Results Machine Learning Humans
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Challenges and Opportunities for Bayesian Statistics in Proteomics.

Journal of proteome research Mar 8, 2022
Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied. For a quantity of ...
Uncertainty Proteomics Probability Bayes Theorem Machine Learning
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Forecasting the realized variance of oil-price returns: a disaggregated analysis of the role of uncertainty and geopolitical risk.

Environmental science and pollution research international Mar 7, 2022
We contribute to the empirical literature on the predictability of oil-market volatility by comparing the predictive role of aggregate versus several disaggregated metrics of policy-related and equity-market uncertainties of the USA and geopolitical ...
Machine Learning Forecasting Petroleum Uncertainty
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Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation.

IEEE journal of biomedical and health informatics Mar 7, 2022
Accurate segmentation of the Intracranial Hemorrhage (ICH) in non-contrast CT images is significant for computer-aided diagnosis. Although existing methods have achieved remarkable 1 1 The code will be available from https://github.com/JohnleeHIT/SLE...
Humans Neural Networks, Computer Uncertainty Hematoma Intracranial Hemorrhages Image Processing, Computer-Assisted
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