AIMC Topic: Machine Learning

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Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers.

Genes
DNA methylation is a process that can affect gene accessibility and therefore gene expression. In this study, a machine learning pipeline is proposed for the prediction of breast cancer and the identification of significant genes that contribute to t...

Synthesising 2D Video from 3D Motion Data for Machine Learning Applications.

Sensors (Basel, Switzerland)
To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames...

End-to-End Continuous/Discontinuous Feature Fusion Method with Attention for Rolling Bearing Fault Diagnosis.

Sensors (Basel, Switzerland)
Mechanical equipment failure may cause massive economic and even life loss. Therefore, the diagnosis of the failures of machine parts in time is crucial. The rolling bearings are one of the most valuable parts, which have attracted the focus of fault...

Efficient enumeration-selection computational strategy for adaptive chemistry.

Scientific reports
Design problems of finding efficient patterns, adaptation of complex molecules to external environments, affinity of molecules to specific targets, dynamic adaptive behavior of chemical systems, reconstruction of 3D structures from diffraction data a...

Semi-supervised classifier guided by discriminator.

Scientific reports
Some machine learning applications do not allow for data augmentation or are applied to modalities where the augmentation is difficult to define. Our study aimed to develop a new method in semi-supervised learning (SSL) applicable to various modaliti...

Optimization of Tennis Teaching Resources and Data Visualization Based on Support Vector Machine.

Computational intelligence and neuroscience
In recent years, with the continuous development of machine learning technology, this technology has achieved success in many fields and activities. Therefore, using machine learning technology for fuzzy research has a good research prospect. In the ...

Design and Purchase Intention Analysis of Cultural and Creative Goods Based on Deep Learning Neural Networks.

Computational intelligence and neuroscience
With the rise of cultural and creative industries, cultural creativity has gradually become an important factor to promote the value of design in the future, and it is also a trend to integrate "cultural elements" into the design of products. At pres...

Stock Portfolio Optimization Using a Combined Approach of Multi Objective Grey Wolf Optimizer and Machine Learning Preselection Methods.

Computational intelligence and neuroscience
The present paper deals with optimizing the stock portfolio of active companies listed on the Tehran Stock Exchange based on the forecast price. This paper is based on a combination of different filtering methods such as optimization of trading rules...

Surgery duration: Optimized prediction and causality analysis.

PloS one
Accurate estimation of duration of surgery (DOS) can lead to cost-effective utilization of surgical staff and operating rooms and decrease patients' waiting time. In this study, we present a supervised DOS nonlinear regression prediction model whose ...

Research on non-destructive testing of hotpot oil quality by fluorescence hyperspectral technology combined with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Eating repeatedly used hotpot oil will cause serious harm to human health. In order to realize rapid non-destructive testing of hotpot oil quality, a modeling experiment method of fluorescence hyperspectral technology combined with machine learning a...