AIMC Topic: Consensus

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Neurodynamic approaches for sparse recovery problem with linear inequality constraints.

Neural networks : the official journal of the International Neural Network Society
This paper develops two neurodynamic approaches for solving the L-minimization problem with the linear inequality constraints. First, a centralized neurodynamic approach is proposed based on projection operator and nonnegative quadrant. The stability...

Artificial intelligence in medical education curriculum: An e-Delphi study for competencies.

PloS one
BACKGROUND: Artificial intelligence (AI) has affected our day-to-day in a great extent. Healthcare industry is one of the mainstream fields among those and produced a noticeable change in treatment and education. Medical students must comprehend well...

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside.

Journal of vascular and interventional radiology : JVIR
Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in ima...

Adaptive-observer-based consensus tracking with fault-tolerant network connectivity of uncertain time-delay nonlinear multiagent systems with actuator and communication faults.

ISA transactions
In this study, a distributed output-feedback design approach for ensuring fault-tolerant initial network connectivity and preselected-time consensus tracking performance is proposed for a class of uncertain time-delay nonlinear multiagent systems (TD...

Performance assessment of ontology matching systems for FAIR data.

Journal of biomedical semantics
BACKGROUND: Ontology matching should contribute to the interoperability aspect of FAIR data (Findable, Accessible, Interoperable, and Reusable). Multiple data sources can use different ontologies for annotating their data and, thus, creating the need...

Distributed Quantized Feedback Design Strategy for Adaptive Consensus Tracking of Uncertain Strict-Feedback Nonlinear Multiagent Systems With State Quantizers.

IEEE transactions on cybernetics
This study investigates a quantized feedback design problem for distributed adaptive leader-following consensus of uncertain strict-feedback nonlinear multiagent systems with state quantizers. It is assumed that all system nonlinearities of followers...

Resilient Delayed Impulsive Control for Consensus of Multiagent Networks Subject to Malicious Agents.

IEEE transactions on cybernetics
Impulsive control is widely applied to achieve the consensus of multiagent networks (MANs). It is noticed that malicious agents may have adverse effects on the global behaviors, which, however, are not taken into account in the literature. In this st...

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

Nature medicine
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluati...

Artificial Intelligence Methods and Artificial Intelligence-Enabled Metrics for Surgical Education: A Multidisciplinary Consensus.

Journal of the American College of Surgeons
BACKGROUND: Artificial intelligence (AI) methods and AI-enabled metrics hold tremendous potential to advance surgical education. Our objective was to generate consensus guidance on specific needs for AI methods and AI-enabled metrics for surgical edu...

DACFL: Dynamic Average Consensus-Based Federated Learning in Decentralized Sensors Network.

Sensors (Basel, Switzerland)
Federated Learning (FL) is a privacy-preserving way to utilize the sensitive data generated by smart sensors of user devices, where a central parameter server (PS) coordinates multiple user devices to train a global model. However, relying on central...