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The use of artificial intelligence and game-based learning in removable partial denture design: A comparative study.

Journal of dental education
PURPOSE: The purpose of this study was to compare student performance in removable partial denture (RPD) design during a pre-clinical RPD course with and without using a recently developed computer software named AiDental. Additionally, student perce...

Stability analysis of stochastic gradient descent for homogeneous neural networks and linear classifiers.

Neural networks : the official journal of the International Neural Network Society
We prove new generalization bounds for stochastic gradient descent when training classifiers with invariances. Our analysis is based on the stability framework and covers both the convex case of linear classifiers and the non-convex case of homogeneo...

FAST skill assessment from kinematics data using convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: FAST is a point of care ultrasound study that evaluates for the presence of free fluid, typically hemoperitoneum in trauma patients. FAST is an essential skill for Emergency Physicians. Thus, it requires objective evaluation tools that can r...

Synthetic Model Combination: A new machine-learning method for pharmacometric model ensembling.

CPT: pharmacometrics & systems pharmacology
When aiming to make predictions over targets in the pharmacological setting, a data-focused approach aims to learn models based on a collection of labeled examples. Unfortunately, data sharing is not always possible, and this can result in many diffe...

Memristor-Based Neural Network Circuit With Multimode Generalization and Differentiation on Pavlov Associative Memory.

IEEE transactions on cybernetics
Most of the classical conditioning laws implemented by existing circuits are involved in learning and forgetting between only three neurons, and the problems between multiple neurons are not considered. In this article, a multimode generalization and...

Optimal H tracking control of nonlinear systems with zero-equilibrium-free via novel adaptive critic designs.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel adaptive critic control method is designed to solve an optimal H tracking control problem for continuous nonlinear systems with nonzero equilibrium based on adaptive dynamic programming (ADP). To guarantee the finiteness of a c...

Basis operator network: A neural network-based model for learning nonlinear operators via neural basis.

Neural networks : the official journal of the International Neural Network Society
It is widely acknowledged that neural networks can approximate any continuous (even measurable) functions between finite-dimensional Euclidean spaces to arbitrary accuracy. Recently, the use of neural networks has started emerging in infinite-dimensi...

Revisiting the video deficit in technology-saturated environments: Successful imitation from people, screens, and social robots.

Journal of experimental child psychology
The "video deficit" is a well-documented effect whereby children learn less well about information delivered via a screen than the same information delivered in person. Research suggests that increasing social contingency may ameliorate this video de...

Learning long-term motor timing/patterns on an orthogonal basis in random neural networks.

Neural networks : the official journal of the International Neural Network Society
The ability of the brain to generate complex spatiotemporal patterns with specific timings is essential for motor learning and temporal processing. An approach that can model this function, using the spontaneous activity of a random neural network (R...

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces.

Journal of chemical information and modeling
This paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest ...