AIMC Topic: Neural Networks, Computer

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Prediction of Human Activities Based on a New Structure of Skeleton Features and Deep Learning Model.

Sensors (Basel, Switzerland)
The recognition of human activities is usually considered to be a simple procedure. Problems occur in complex scenes involving high speeds. Activity prediction using Artificial Intelligence (AI) by numerical analysis has attracted the attention of se...

Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees.

Journal of healthcare engineering
PURPOSE: To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clini...

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Computational and mathematical methods in medicine
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method fo...

Extracting Parallel Sentences from Nonparallel Corpora Using Parallel Hierarchical Attention Network.

Computational intelligence and neuroscience
Collecting parallel sentences from nonparallel data is a long-standing natural language processing research problem. In particular, parallel training sentences are very important for the quality of machine translation systems. While many existing met...

Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND: Although great advances in artificial intelligence for interpreting small bowel capsule endoscopy (SBCE) images have been made in recent years, its practical use is still limited. The aim of this study was to develop a more practical conv...

Pathway-Guided Deep Neural Network toward Interpretable and Predictive Modeling of Drug Sensitivity.

Journal of chemical information and modeling
To efficiently save cost and reduce risk in drug research and development, there is a pressing demand to develop methods to predict drug sensitivity to cancer cells. With the exponentially increasing number of multi-omics data derived from high-thro...

Fault Diagnosis for High-Speed Train Axle-Box Bearing Using Simplified Shallow Information Fusion Convolutional Neural Network.

Sensors (Basel, Switzerland)
Axle-box bearings are one of the most critical mechanical components of the high-speed train. Vibration signals collected from axle-box bearings are usually nonlinear and nonstationary, caused by the complicated operating conditions. Due to the high ...

Estimation of Ultrasound Echogenicity Map from B-Mode Images Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
In ultrasound B-mode imaging, speckle noises decrease the accuracy of estimation of tissue echogenicity of imaged targets from the amplitude of the echo signals. In addition, since the granular size of the speckle pattern is affected by the point spr...

Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

JMIR mHealth and uHealth
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early ...