AIMC Topic: Uncertainty

Clear Filters Showing 421 to 430 of 706 articles

Equivalent-input-disturbance estimator-based event-triggered control design for master-slave neural networks.

Neural networks : the official journal of the International Neural Network Society Jun 29, 2021
This paper investigates the robust synchronization problem for a class of master-slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) esti...
Uncertainty Communication Time Factors Neural Networks, Computer
View on PubMed DOI

Self-paced and self-consistent co-training for semi-supervised image segmentation.

Medical image analysis Jun 26, 2021
Deep co-training has recently been proposed as an effective approach for image segmentation when annotated data is scarce. In this paper, we improve existing approaches for semi-supervised segmentation with a self-paced and self-consistent co-trainin...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Supervised Machine Learning Entropy Uncertainty
View on PubMed DOI

Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound.

Medical image analysis Jun 22, 2021
Segmentation of ovary and follicles from 3D ultrasound (US) is the crucial technique of measurement tools for female infertility diagnosis. Since manual segmentation is time-consuming and operator-dependent, an accurate and fast segmentation method i...
Ovary Uncertainty Benchmarking Supervised Machine Learning Humans Female Ultrasonography
View on PubMed DOI

BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

Risk analysis : an official publication of the Society for Risk Analysis Jun 19, 2021
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificia...
Humans Uncertainty Bayes Theorem Problem Solving Artificial Intelligence Software
View on PubMed DOI

Assigning confidence to molecular property prediction.

Expert opinion on drug discovery Jun 15, 2021
: Computational modeling has rapidly advanced over the last decades. Recently, machine learning has emerged as a powerful and cost-effective strategy to learn from existing datasets and perform predictions on unseen molecules. Accordingly, the explos...
Humans Drug Design Machine Learning Computer Simulation Uncertainty
View on PubMed DOI

How to handle noisy labels for robust learning from uncertainty.

Neural networks : the official journal of the International Neural Network Society Jun 12, 2021
Most deep neural networks (DNNs) are trained with large amounts of noisy labels when they are applied. As DNNs have the high capacity to fit any noisy labels, it is known to be difficult to train DNNs robustly with noisy labels. These noisy labels ca...
Uncertainty Neural Networks, Computer Algorithms
View on PubMed DOI

Choosing a Metamodel of a Simulation Model for Uncertainty Quantification.

Medical decision making : an international journal of the Society for Medical Decision Making Jun 8, 2021
BACKGROUND: Metamodeling may substantially reduce the computational expense of individual-level state transition simulation models (IL-STM) for calibration, uncertainty quantification, and health policy evaluation. However, because of the lack of gui...
Humans Neural Networks, Computer Computer Simulation Linear Models Normal Distribution Uncertainty
View on PubMed DOI

Deep Learning-Based Conformal Prediction of Toxicity.

Journal of chemical information and modeling May 27, 2021
Predictive modeling for toxicity can help reduce risks in a range of applications and potentially serve as the basis for regulatory decisions. However, the utility of these predictions can be limited if the associated uncertainty is not adequately qu...
Humans Neural Networks, Computer Machine Learning Deep Learning Molecular Conformation Uncertainty
View on PubMed DOI

A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy.

Medical image analysis May 17, 2021
In post-operative radiotherapy for prostate cancer, precisely contouring the clinical target volume (CTV) to be irradiated is challenging, because the cancerous prostate gland has been surgically removed, so the CTV encompasses the microscopic spread...
Radiotherapy Planning, Computer-Assisted Deep Learning Tomography, X-Ray Computed Prostatic Neoplasms Male Uncertainty Humans
View on PubMed DOI

Artificial intelligence for classifying uncertain images by humans in determining choroidal vascular running pattern and comparisons with automated classification between artificial intelligence.

PloS one May 14, 2021
PURPOSE: Abnormalities of the running pattern of choroidal vessel have been reported in eyes with pachychoroid diseases. However, it is difficult for clinicians to judge the running pattern with high reproducibility. Thus, the purpose of this study w...
Tomography, Optical Coherence Aged Choroid Diseases Uncertainty Young Adult Artificial Intelligence Humans Image Processing, Computer-Assisted Adult Retrospective Studies Choroid Middle Aged
View on PubMed DOI
Popular Topics
Recent Journals