AIMC Topic: Neural Networks, Computer

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Global polynomial periodicity and polynomial stability of proportional delay Cohen-Grossberg neural networks.

ISA transactions
This paper tackles the global polynomial periodicity (GPP) and global polynomial stability (GPS) for proportional delay Cohen-Grossberg neural networks (PDCGNNs). By adopting two transformations, designing opportune Lyapunov functionals (LFs) with tu...

Bingham deep neural and oppositional fish swarm optimized protein structure prediction.

Journal of biomolecular structure & dynamics
It is familiar that essential proteins take part in managing cellular activities in living organisms. Moreover, protein structure prediction from its amino acid sequence is advantageous to the comprehending of cellular functions. Formerly, several es...

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.

Computers in biology and medicine
Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The objective of affective computing is to recognize different types of emotions for human-computer inte...

Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics.

Nature neuroscience
Decades of neurobiological research have disclosed the diverse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysi...

Pig Weight and Body Size Estimation Using a Multiple Output Regression Convolutional Neural Network: A Fast and Fully Automatic Method.

Sensors (Basel, Switzerland)
Pig weight and body size are important indicators for producers. Due to the increasing scale of pig farms, it is increasingly difficult for farmers to quickly and automatically obtain pig weight and body size. Due to this problem, we focused on a mul...

Understanding inherent image features in CNN-based assessment of diabetic retinopathy.

Scientific reports
Diabetic retinopathy (DR) is a leading cause of blindness and affects millions of people throughout the world. Early detection and timely checkups are key to reduce the risk of blindness. Automated grading of DR is a cost-effective way to ensure earl...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Scientific reports
Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral quantitative computed tomography (HR-pQCT) allows the quantification of volumetric bone mineral density...

Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer.

BJU international
OBJECTIVE: To develop a new digital biomarker based on the analysis of primary tumour tissue by a convolutional neural network (CNN) to predict lymph node metastasis (LNM) in a cohort matched for already established risk factors.

Convolutional neural network analysis of recurrence plots for high resolution melting classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, bacteria, yeast, virus, etc. HRM data are produced using real-time polymerase chain reaction (PCR) a...

Prediction of weaning from mechanical ventilation using Convolutional Neural Networks.

Artificial intelligence in medicine
Weaning from mechanical ventilation covers the process of liberating the patient from mechanical support and removing the associated endotracheal tube. The management of weaning from mechanical ventilation comprises a significant proportion of the ca...