AIMC Topic: Neural Networks, Computer

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Learning precise spatiotemporal sequences via biophysically realistic learning rules in a modular, spiking network.

eLife
Multiple brain regions are able to learn and express temporal sequences, and this functionality is an essential component of learning and memory. We propose a substrate for such representations via a network model that learns and recalls discrete seq...

Automated segmentation of an intensity calibration phantom in clinical CT images using a convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: In quantitative computed tomography (CT), manual selection of the intensity calibration phantom's region of interest is necessary for calculating density (mg/cm) from the radiodensity values (Hounsfield units: HU). However, as this manual pr...

Semi-dilated convolutional neural networks for epileptic seizure prediction.

Neural networks : the official journal of the International Neural Network Society
Epilepsy is a neurological brain disorder that affects ∼75 million people worldwide. Predicting epileptic seizures holds great potential for improving the quality of life of people with epilepsy, but seizure prediction solely from the Electroencephal...

Extracting Biomedical Entity Relations using Biological Interaction Knowledge.

Interdisciplinary sciences, computational life sciences
Discovering relations of cross-type biomedical entities is crucial for biology research. A large amount of potential or indirect connected biological relations is hidden in millions of biomedical literatures and biological databases. The previous rul...

A novel method for clinical risk prediction with low-quality data.

Artificial intelligence in medicine
In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital readmission, and chronic disease onset) are constantly struggling with low-quality issues, namely redundant and highly correlated features, extreme cat...

Machine Learning for Accurate Intraoperative Pediatric Middle Ear Effusion Diagnosis.

Pediatrics
OBJECTIVES: Misdiagnosis of acute and chronic otitis media in children can result in significant consequences from either undertreatment or overtreatment. Our objective was to develop and train an artificial intelligence algorithm to accurately predi...

Cascaded MultiTask 3-D Fully Convolutional Networks for Pancreas Segmentation.

IEEE transactions on cybernetics
Automatic pancreas segmentation is crucial to the diagnostic assessment of diabetes or pancreatic cancer. However, the relatively small size of the pancreas in the upper body, as well as large variations of its location and shape in retroperitoneum, ...

An Inception Convolutional Autoencoder Model for Chinese Healthcare Question Clustering.

IEEE transactions on cybernetics
Healthcare question answering (HQA) system plays a vital role in encouraging patients to inquire for professional consultation. However, there are some challenging factors in learning and representing the question corpus of HQA datasets, such as high...

Predicting Proteolysis in Complex Proteomes Using Deep Learning.

International journal of molecular sciences
Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins t...

Action detection using a neural network elucidates the genetics of mouse grooming behavior.

eLife
Automated detection of complex animal behaviors remains a challenging problem in neuroscience, particularly for behaviors that consist of disparate sequential motions. Grooming is a prototypical stereotyped behavior that is often used as an endopheno...