AIMC Topic: Neural Networks, Computer

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A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis.

Neural computation
Cortical pyramidal neurons receive inputs from multiple distinct neural populations and integrate these inputs in separate dendritic compartments. We explore the possibility that cortical microcircuits implement canonical correlation analysis (CCA), ...

Do Neural Networks for Segmentation Understand Insideness?

Neural computation
The insideness problem is an aspect of image segmentation that consists of determining which pixels are inside and outside a region. Deep neural networks (DNNs) excel in segmentation benchmarks, but it is unclear if they have the ability to solve the...

Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization.

Neural computation
Learning new concepts rapidly from a few examples is an open issue in spike-based machine learning. This few-shot learning imposes substantial challenges to the current learning methodologies of spiking neuron networks (SNNs) due to the lack of task-...

RNAProt: an efficient and feature-rich RNA binding protein binding site predictor.

GigaScience
BACKGROUND: Cross-linking and immunoprecipitation followed by next-generation sequencing (CLIP-seq) is the state-of-the-art technique used to experimentally determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). However, it relies...

The attention schema theory in a neural network agent: Controlling visuospatial attention using a descriptive model of attention.

Proceedings of the National Academy of Sciences of the United States of America
In the attention schema theory (AST), the brain constructs a model of attention, the attention schema, to aid in the endogenous control of attention. Growing behavioral evidence appears to support the presence of a model of attention. However, a cent...

Biomedical and clinical English model packages for the Stanza Python NLP library.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to develop and evaluate neural natural language processing (NLP) packages for the syntactic analysis and named entity recognition of biomedical and clinical English text.

Multitask prediction of organ dysfunction in the intensive care unit using sequential subnetwork routing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Multitask learning (MTL) using electronic health records allows concurrent prediction of multiple endpoints. MTL has shown promise in improving model performance and training efficiency; however, it often suffers from negative transfer - i...

How multisensory neurons solve causal inference.

Proceedings of the National Academy of Sciences of the United States of America
Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult chal...

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

European heart journal
AIMS: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-en...

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology.

Plant physiology
The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual an...