AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Uncertainty

Showing 391 to 400 of 667 articles

Clear Filters

Active sensing with artificial neural networks.

Neural networks : the official journal of the International Neural Network Society
The fitness of behaving agents depends on their knowledge of the environment, which demands efficient exploration strategies. Active sensing formalizes exploration as reduction of uncertainty about the current state of the environment. Despite strong...

A stochastic modeling approach for analyzing water resources systems.

Journal of contaminant hydrology
Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated th...

Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Brain ageing is a complex neurobiological process associated with morphological changes that can be assessed on MRI scans. Recently, Deep learning (DL)-based approaches have been proposed for the prediction of chronological brain age from MR images y...

Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search.

Journal of chemical information and modeling
Machine learning (ML) plays a growing role in the design and discovery of chemicals, aiming to reduce the need to perform expensive experiments and simulations. ML for such applications is promising but difficult, as models must generalize to vast ch...

RCoNet: Deformable Mutual Information Maximization and High-Order Uncertainty-Aware Learning for Robust COVID-19 Detection.

IEEE transactions on neural networks and learning systems
The novel 2019 Coronavirus (COVID-19) infection has spread worldwide and is currently a major healthcare challenge around the world. Chest computed tomography (CT) and X-ray images have been well recognized to be two effective techniques for clinical...

The absorption and multiplication of uncertainty in machine-learning-driven finance.

The British journal of sociology
Uncertainty about market developments and their implications characterize financial markets. Increasingly, machine learning is deployed as a tool to absorb this uncertainty and transform it into manageable risk. This article analyses machine-learning...

Adaptive robust synchronized control for cooperative robotic manipulators with uncertain base coordinate system.

ISA transactions
In this paper, cooperative robotic manipulators under uncertain base coordinate are investigated. The coordinate uncertainties result in biases of cooperative robotic dynamics, which involve horizontal and vertical translational errors in the task sp...

Explaining distortions in metacognition with an attractor network model of decision uncertainty.

PLoS computational biology
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that mo...

Bayesian Fully Convolutional Networks for Brain Image Registration.

Journal of healthcare engineering
The purpose of medical image registration is to find geometric transformations that align two medical images so that the corresponding voxels on two images are spatially consistent. Nonrigid medical image registration is a key step in medical image p...

Exploring the potential of utilizing unsupervised machine learning for urban drainage sensor placement under future rainfall uncertainty.

Journal of environmental management
Recently, advanced informatics and sensing techniques show promise of enabling a new generation of smart stormwater systems, where real-time sensors are deployed to detect flooding hotspots. Existing stormwater design criteria assume that historical ...