AIMC Topic: Data Analysis

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A survey on gene expression data analysis using deep learning methods for cancer diagnosis.

Progress in biophysics and molecular biology
Gene Expression Data is the biological data to extract meaningful hidden information from the gene dataset. This gene information is used for disease diagnosis especially in cancer treatment based on the variations in gene expression levels. DNA micr...

Design and Optimization of Aesthetic Education Teaching Information Platform Based on Big Data Analysis.

Computational intelligence and neuroscience
In the process of promoting school aesthetic education, some schools have some problems, such as insufficient construction of campus aesthetic education environment, lack of aesthetic thinking in various disciplines, and so on. In view of these probl...

Construction of Digital Platform of Religious and Cultural Resources Using Deep Learning and Its Big Data Analysis.

Computational intelligence and neuroscience
This article analyzes the difficulties associated with the preservation and transmission of religious cultural resources and the difficulties encountered in the new development environment and background. It does so in light of the current state of r...

AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning.

Journal of synchrotron radiation
The Argonne X-ray Emission Analysis Package (AXEAP) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into...

Use of SVM-based ensemble feature selection method for gene expression data analysis.

Statistical applications in genetics and molecular biology
Gene selection is one of the key steps for gene expression data analysis. An SVM-based ensemble feature selection method is proposed in this paper. Firstly, the method builds many subsets by using Monte Carlo sampling. Secondly, ranking all the featu...

Visible Particle Identification Using Raman Spectroscopy and Machine Learning.

AAPS PharmSciTech
Visible particle identification is a crucial prerequisite step for process improvement and control during the manufacturing of injectable biotherapeutic drug products. Raman spectroscopy is a technology with several advantages for particle identifica...

Optimization of Imbalanced and Multidimensional Learning Under Bayes Minimum Risk and Savings Measure.

Big data
The full potential of data analysis is crippled by imbalanced and high-dimensional data, which makes these topics significantly important. Consequently, substantial research efforts have been directed to obtain dimension reduction and resolve data im...

Construction of Tourism E-Commerce Platform Based on Artificial Intelligence Algorithm.

Computational intelligence and neuroscience
In the late twentieth century, with the rapid development of the Internet, e-commerce has emerged rapidly, which has changed the way people travel around the world. The greatest advantages of e-commerce are the flow of information and data and the im...

Gene expression data classification using topology and machine learning models.

BMC bioinformatics
BACKGROUND: Interpretation of high-throughput gene expression data continues to require mathematical tools in data analysis that recognizes the shape of the data in high dimensions. Topological data analysis (TDA) has recently been successful in extr...

Data Analysis and Knowledge Mining of Machine Learning in Soil Corrosion Factors of the Pipeline Safety.

Computational intelligence and neuroscience
The purpose of this research is to enhance the ability of data analysis and knowledge mining in soil corrosion factors of the pipeline. According to its multifactor characteristics, the rough set algorithm is directly used to analyze and process the ...