AIMC Topic: Neural Networks, Computer

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[An artificial neural network diagnostic model for scleroderma and immune cell infiltration analysis based on mitochondria-associated genes].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.

[Neural network analysis of mechanization's impact on coal miner's occupational health].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence for the development of new quality productivity in the coal industry that balances health and efficie...

Development and external validation of deep learning clinical prediction models using variable-length time series data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To compare and externally validate popular deep learning model architectures and data transformation methods for variable-length time series data in 3 clinical tasks (clinical deterioration, severe acute kidney injury [AKI], and suspected...

A prostate seed implantation robot system based on human-computer interactions: Augmented reality and voice control.

Mathematical biosciences and engineering : MBE
The technology of robot-assisted prostate seed implantation has developed rapidly. However, during the process, there are some problems to be solved, such as non-intuitive visualization effects and complicated robot control. To improve the intelligen...

Prediction of drug-protein interaction based on dual channel neural networks with attention mechanism.

Briefings in functional genomics
The precise identification of drug-protein inter action (DPI) can significantly speed up the drug discovery process. Bioassay methods are time-consuming and expensive to screen for each pair of drug proteins. Machine-learning-based methods cannot acc...

AttBiLFNet: A novel hybrid network for accurate and efficient arrhythmia detection in imbalanced ECG signals.

Mathematical biosciences and engineering : MBE
Within the domain of cardiovascular diseases, arrhythmia is one of the leading anomalies causing sudden deaths. These anomalies, including arrhythmia, are detectable through the electrocardiogram, a pivotal component in the analysis of heart diseases...

Computationally Efficient Demographic History Inference from Allele Frequencies with Supervised Machine Learning.

Molecular biology and evolution
Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele...

In vivo neuropil density from anatomical MRI and machine learning.

Cerebral cortex (New York, N.Y. : 1991)
Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from ...

Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.

Bioinformatics (Oxford, England)
MOTIVATION: Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitne...

Chainsaw: protein domain segmentation with fully convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Protein domains are fundamental units of protein structure and play a pivotal role in understanding folding, function, evolution, and design. The advent of accurate structure prediction techniques has resulted in an influx of new structur...