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Uncertainty

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Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Medical image analysis
Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the leading causes of cancer-related deaths on a global scale. Early detection and prevention of colorectal cancer is primarily enabled through manual screen...

Accuracy, uncertainty, and adaptability of automatic myocardial ASL segmentation using deep CNN.

Magnetic resonance in medicine
PURPOSE: To apply deep convolution neural network to the segmentation task in myocardial arterial spin labeled perfusion imaging and to develop methods that measure uncertainty and that adapt the convolution neural network model to a specific false-p...

Land Suitability Evaluation and an Interval Stochastic Fuzzy Programming-Based Optimization Model for Land-Use Planning and Environmental Policy Analysis.

International journal of environmental research and public health
People explosion and fast economic growth are bringing a more serious land resource shortage crisis. Rational land-use allocation can effectively reduce this burden. Existing land-use allocation models may deal with a lot of challenges of land-use pl...

Uncertainty-based modulation for lifelong learning.

Neural networks : the official journal of the International Neural Network Society
The creation of machine learning algorithms for intelligent agents capable of continuous, lifelong learning is a critical objective for algorithms being deployed on real-life systems in dynamic environments. Here we present an algorithm inspired by n...

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Scientific reports
Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely a...

Event-triggered passivity and synchronization of delayed multiple-weighted coupled reaction-diffusion neural networks with non-identical nodes.

Neural networks : the official journal of the International Neural Network Society
This paper solves the event-triggered passivity and synchronization problems for delayed multiple-weighted coupled reaction-diffusion neural networks (DMWCRDNNs) composed of non-identical nodes with and without parameter uncertainties. On one side, b...

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation.

Medical image analysis
Deep learning networks have recently been shown to outperform other segmentation methods on various public, medical-image challenge datasets, particularly on metrics focused on large pathologies. For diseases such as Multiple Sclerosis (MS), however,...

Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning.

International journal of radiation oncology, biology, physics
PURPOSE: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network [GAN]) usin...

Physics-driven learning of x-ray skin dose distribution in interventional procedures.

Medical physics
PURPOSE: Radiation doses accumulated during very complicated image-guided x-ray procedures have the potential to cause stochastic, but also deterministic effects, such as skin rashes or even hair loss. To monitor and reduce radiation-related risks to...

Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method.

BMC medical informatics and decision making
BACKGROUND: Kidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the medical aspects. Leading countries in this field use a point scoring system to allocate kidneys. Hence...