AIMC Topic: Association

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Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists.

Journal of medical Internet research Jun 22, 2020
Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are no...
Artificial Intelligence Machine Learning Physicians Humans Diabetes Mellitus Italy Association Clinical Decision-Making Big Data Precision Medicine
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New approach to global Mittag-Leffler synchronization problem of fractional-order quaternion-valued BAM neural networks based on a new inequality.

Neural networks : the official journal of the International Neural Network Society Nov 4, 2019
In this paper, a novel kind of neural networks named fractional-order quaternion-valued bidirectional associative memory neural networks (FQVBAMNNs) is formulated. On one hand, applying Hamilton rules in quaternion multiplication which is essentially...
Association Algorithms Memory Neural Networks, Computer
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Modeling of Brain-Like Concept Coding with Adulthood Neurogenesis in the Dentate Gyrus.

Computational intelligence and neuroscience Nov 3, 2019
Mammalian brains respond to new concepts via a type of neural coding termed "concept coding." During concept coding, the dentate gyrus (DG) plays a vital role in pattern separation and pattern integration of concepts because it is a brain region with...
Neurons Concept Formation Dentate Gyrus Association Neurogenesis Neuronal Plasticity Models, Neurological Action Potentials Computer Simulation Humans Animals Neural Networks, Computer
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Design and development of a robotic predator as a stimulus in conditioned place aversion for the study of the effect of ethanol and citalopram in zebrafish.

Behavioural brain research Oct 12, 2019
Zebrafish are becoming a species of choice in psychopharmacology, laying a promising path to refined pharmacological manipulations and high-throughput behavioral phenotyping. The field of robotics has the potential to accelerate progress along this p...
Male Ethanol Robotics Female Animals Behavior, Animal Fear Conditioning, Psychological Equipment Design Zebrafish Selective Serotonin Reuptake Inhibitors Central Nervous System Depressants Spatial Behavior Association Predatory Behavior Citalopram Avoidance Learning
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The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control.

PloS one Sep 24, 2018
In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into...
Neural Networks, Computer Mathematical Concepts Models, Neurological Brain Humans Systems Theory Nerve Net Computer Simulation Association Models, Psychological Memory Time Factors
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Memory States and Transitions between Them in Attractor Neural Networks.

Neural computation Aug 4, 2017
Human memory is capable of retrieving similar memories to a just retrieved one. This associative ability is at the base of our everyday processing of information. Current models of memory have not been able to underpin the mechanism that the brain co...
Memory Association Brain Models, Neurological Neurons Humans Neural Networks, Computer
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A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State.

Computational intelligence and neuroscience Nov 3, 2016
Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a h...
Models, Theoretical Algorithms Environment Markov Chains Humans Memory Association Computer Simulation Time Factors Neural Networks, Computer
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Semantics derived automatically from language corpora contain human-like biases.

Science (New York, N.Y.) Apr 14, 2017
Machine learning is a means to derive artificial intelligence by discovering patterns in existing data. Here, we show that applying machine learning to ordinary human language results in human-like semantic biases. We replicated a spectrum of known b...
Language Humans Semantics Female Machine Learning Names Internet Male Association Sex Factors
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