AIMC Topic: Neural Networks, Computer

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A Systematic Review of Detecting Sleep Apnea Using Deep Learning.

Sensors (Basel, Switzerland)
Sleep apnea is a sleep related disorder that significantly affects the population. Polysomnography, the gold standard, is expensive, inaccessible, uncomfortable and an expert technician is needed to score. Numerous researchers have proposed and imple...

Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos.

Scientific reports
The present study aimed to conduct a real-time automatic analysis of two important surgical phases, which are continuous curvilinear capsulorrhexis (CCC), nuclear extraction, and three other surgical phases of cataract surgery using artificial intell...

Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.

PloS one
This study presents a novel research approach to predict user interaction for social media post using machine learning algorithms. The posts are converted to vector form using word2vec and doc2vec model. These two methods are used to analyse the best...

Self-attention based recurrent convolutional neural network for disease prediction using healthcare data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Nowadays computer-aided disease diagnosis from medical data through deep learning methods has become a wide area of research. Existing works of analyzing clinical text data in the medical domain, which substantiate useful in...

Adaptive Calibration of Electrode Array Shifts Enables Robust Myoelectric Control.

IEEE transactions on bio-medical engineering
OBJECTIVE: The objective of this work is to develop a novel method for adaptive calibration of the electrode array shifts toward achieving robust myoelectric pattern-recognition control.

Application of Deep Compression Technique in Spiking Neural Network Chip.

IEEE transactions on biomedical circuits and systems
In this paper, a reconfigurable and scalable spiking neural network processor, containing 192 neurons and 6144 synapses, is developed. By using deep compression technique in spiking neural network chip, the amount of physical synapses can be reduced ...

New grading criterion for retinal haemorrhages in term newborns based on deep convolutional neural networks.

Clinical & experimental ophthalmology
BACKGROUND: To define a new quantitative grading criterion for retinal haemorrhages in term newborns based on the segmentation results of a deep convolutional neural network.

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...

DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...

A Multibranch Object Detection Method for Traffic Scenes.

Computational intelligence and neuroscience
The performance of convolutional neural network- (CNN-) based object detection has achieved incredible success. Howbeit, existing CNN-based algorithms suffer from a problem that small-scale objects are difficult to detect because it may have lost its...