AIMC Topic: Neural Networks, Computer

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Capsules for biomedical image segmentation.

Medical image analysis
Our work expands the use of capsule networks to the task of object segmentation for the first time in the literature. This is made possible via the introduction of locally-constrained routing and transformation matrix sharing, which reduces the param...

PM2.5 concentration modeling and prediction by using temperature-based deep belief network.

Neural networks : the official journal of the International Neural Network Society
Air quality prediction is a global hot issue, and PM is an important factor affecting air quality. Due to complicated causes of formation, PM prediction is a thorny and challenging task. In this paper, a novel deep learning model named temperature-ba...

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...

A Systematic Literature Review of the Successors of "NeuroEvolution of Augmenting Topologies".

Evolutionary computation
NeuroEvolution (NE) refers to a family of methods for optimizing Artificial Neural Networks (ANNs) using Evolutionary Computation (EC) algorithms. NeuroEvolution of Augmenting Topologies (NEAT) is considered one of the most influential algorithms in ...

A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) in various medical imaging tasks. However, in computed tomographic (CT) colonography, the performance is limited by the relatively small size and the ...

Deep Learning on chromatographic data for Segmentation and Sensitive Analysis.

Journal of chromatography. A
Lateral flow immunoassay (LFIA) is one of the most common methods in point-of-care testing, which is widely applied in some conditions for various applications. Image segmentation is an increasingly popular experimental paradigm to efficiently test t...

A medical percussion instrument using a wavelet-based method for archivable output and automatic classification.

Computers in biology and medicine
There is no standard instrument for carrying out medical percussion even though the procedure has been in continuous use since 1761. This study developed one such instrument. It generates medical percussion sounds in a reproducible manner and accurat...

A modeling framework for adaptive lifelong learning with transfer and savings through gating in the prefrontal cortex.

Proceedings of the National Academy of Sciences of the United States of America
The prefrontal cortex encodes and stores numerous, often disparate, schemas and flexibly switches between them. Recent research on artificial neural networks trained by reinforcement learning has made it possible to model fundamental processes underl...

Unsupervised and supervised learning with neural network for human transcriptome analysis and cancer diagnosis.

Scientific reports
Deep learning analysis of images and text unfolds new horizons in medicine. However, analysis of transcriptomic data, the cause of biological and pathological changes, is hampered by structural complexity distinctive from images and text. Here we con...

Cumulative learning enables convolutional neural network representations for small mass spectrometry data classification.

Nature communications
Rapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these ...