AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28191 to 28200 of 31376 articles

HimGNN: a novel hierarchical molecular graph representation learning framework for property prediction.

Briefings in bioinformatics
Accurate prediction of molecular properties is an important topic in drug discovery. Recent works have developed various representation schemes for molecular structures to capture different chemical information in molecules. The atom and motif can be...

Predicting metabolite-disease associations based on auto-encoder and non-negative matrix factorization.

Briefings in bioinformatics
Metabolism refers to a series of orderly chemical reactions used to maintain life activities in organisms. In healthy individuals, metabolism remains within a normal range. However, specific diseases can lead to abnormalities in the levels of certain...

Prediction of postoperative complications after oesophagectomy using machine-learning methods.

The British journal of surgery
BACKGROUND: Oesophagectomy is an operation with a high risk of postoperative complications. The aim of this single-centre retrospective study was to apply machine-learning methods to predict complications (Clavien-Dindo grade IIIa or higher) and spec...

AFsample: improving multimer prediction with AlphaFold using massive sampling.

Bioinformatics (Oxford, England)
SUMMARY: The AlphaFold2 neural network model has revolutionized structural biology with unprecedented performance. We demonstrate that by stochastically perturbing the neural network by enabling dropout at inference combined with massive sampling, it...

The Deep Generative Decoder: MAP estimation of representations improves modelling of single-cell RNA data.

Bioinformatics (Oxford, England)
MOTIVATION: Learning low-dimensional representations of single-cell transcriptomics has become instrumental to its downstream analysis. The state of the art is currently represented by neural network models, such as variational autoencoders, which us...

Hybrid Rehabilitation System with Motion Estimation Based on EMG Signals.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Patients with upper limb paralysis undergo various types of rehabilitation to reconstruct upper limb functions necessary for their return to daily life and social activities. Therefore, it is necessary to develop an effective rehabilitation support s...

Automated Patient-Robot Task Assignment in a Simulated Stochastic Rehabilitation Gym.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Rehabilitation after neurological injury can be provided by robots that help patients perform different exercises. Multiple such robots can be combined in a rehabilitation robot gym to allow multiple patients to perform a diverse range of exercises s...

Beautification of images by generative adversarial networks.

Journal of vision
Finding the properties underlying beauty has always been a prominent yet difficult problem. However, new technological developments have often aided scientific progress by expanding the scientists' toolkit. Currently in the spotlight of cognitive neu...

A regression model combined convolutional neural network and recurrent neural network for electroencephalogram-based cross-subject fatigue detection.

The Review of scientific instruments
Fatigue, one of the most important factors affecting road safety, has attracted many researchers' attention. Most existing fatigue detection methods are based on feature engineering and classification models. The feature engineering is greatly influe...