AIMC Topic: Consensus

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Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit.

BMC neurology
INTRODUCTION: Digital twins, a form of artificial intelligence, are virtual representations of the physical world. In the past 20 years, digital twins have been utilized to track wind turbines' operations, monitor spacecraft's status, and even create...

Improved disturbance observer-based fixed-time adaptive neural network consensus tracking for nonlinear multi-agent systems.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems subject to unknown disturbances. Firstly, a modified fixed-time disturbance observer is devised to estimate the unknown mismatched ...

Robust Multi-Sensor Consensus Plant Disease Detection Using the Choquet Integral.

Sensors (Basel, Switzerland)
Over the last few years, several studies have appeared that employ Artificial Intelligence (AI) techniques to improve sustainable development in the agricultural sector. Specifically, these intelligent techniques provide mechanisms and procedures to ...

A neurodynamic approach for nonsmooth optimal power consumption of intelligent and connected vehicles.

Neural networks : the official journal of the International Neural Network Society
This paper investigates a class of power consumption minimization and equalization for intelligent and connected vehicles cooperative system. Accordingly, a distributed optimization problem model related to power consumption and data rate of intellig...

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach.

Scientific reports
Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and ...

Utilizing a Digital Swarm Intelligence Platform to Improve Consensus Among Radiologists and Exploring Its Applications.

Journal of digital imaging
Radiologists today play a central role in making diagnostic decisions and labeling images for training and benchmarking artificial intelligence (AI) algorithms. A key concern is low inter-reader reliability (IRR) seen between experts when interpretin...

A New Consensus Model Based on Trust Interactive Weights for Intuitionistic Group Decision Making in Social Networks.

IEEE transactions on cybernetics
A promising feature for group decision making (GDM) lies in the study of the interaction between individuals. In conventional GDM research, experts are independent. This is reflected in the setting of preferences and weights. Nevertheless, each exper...

MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery.

Journal of chemical information and modeling
Molecular docking tools are regularly used to computationally identify new molecules in virtual screening for drug discovery. However, docking tools suffer from inaccurate scoring functions with widely varying performance on different proteins. To en...

An Additive Consistency and Consensus Approach for Group Decision Making With Probabilistic Hesitant Fuzzy Linguistic Preference Relations and Its Application in Failure Criticality Analysis.

IEEE transactions on cybernetics
In this article, probabilistic hesitant fuzzy linguistic preference relations (PHFLPRs) are proposed to present the qualitative pairwise preference information of decision makers (DMs) with hesitation and probability uncertainty assessments. The meas...

International Expert Consensus on Metric-based Characterization of Robot-assisted Partial Nephrectomy.

European urology focus
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) training usually takes place in vivo, and methods vary across countries/institutions. No common system exists to objectively assess trainee ability to perform RAPN at predetermined performance lev...