One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

Furthermore, our method is generalizable, which can be applied to various network structures, such as multilayer perceptron (MLP), convolutional neural networks (CNNs), recurrent neural networks (RNNs ...

SARPLLM leverages large language modeling and quantum algorithms to predict Salmonella AMR, offering robust analysis and user ...

This project aims to select optimal NFL team players from a pool of active and retired players using a Multi-Layer Perceptron (MLP) Artificial Neural Network. The players are evaluated across various ...

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Methods: This study proposes a graph convolutional neural network (GCN)-based ADHD detection framework utilizing multi-domain electroencephalogram (EEG) features. First, time-domain and ...