AIMC Topic: Data Analysis
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Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms.
PloS one
Jun 22, 2021
The aims are to improve the efficiency in analyzing the regional economic changes in China's high-tech industrial development zones (IDZs), ensure the industrial structural integrity, and comprehensively understand the roles of capital, technology, a...
Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.
BMC bioinformatics
Jun 11, 2021
BACKGROUND: Drug-drug interaction (DDI) is a serious public health issue. The L1000 database of the LINCS project has collected millions of genome-wide expressions induced by 20,000 small molecular compounds on 72 cell lines. Whether this unified and...
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.
Molecular diversity
May 24, 2021
Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing...
Multiomic Big Data Analysis Challenges: Increasing Confidence in the Interpretation of Artificial Intelligence Assessments.
Analytical chemistry
May 24, 2021
The need for holistic molecular measurements to better understand disease initiation, development, diagnosis, and therapy has led to an increasing number of multiomic analyses. The wealth of information available from multiomic assessments, however, ...
A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.
Journal of medical Internet research
May 20, 2021
BACKGROUND: More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the glob...
Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires.
eLife
May 14, 2021
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...
Activation patterns of interictal epileptiform discharges in relation to sleep and seizures: An artificial intelligence driven data analysis.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
May 8, 2021
OBJECTIVE: To quantify effects of sleep and seizures on the rate of interictal epileptiform discharges (IED) and to classify patients with epilepsy based on IED activation patterns.
Pure Ion Chromatograms Combined with Advanced Machine Learning Methods Improve Accuracy of Discriminant Models in LC-MS-Based Untargeted Metabolomics.
Molecules (Basel, Switzerland)
May 5, 2021
Untargeted metabolomics based on liquid chromatography coupled with mass spectrometry (LC-MS) can detect thousands of features in samples and produce highly complex datasets. The accurate extraction of meaningful features and the building of discrimi...
Leveraging Automated Machine Learning for the Analysis of Global Public Health Data: A Case Study in Malaria.
International journal of public health
Apr 13, 2021
The Saudi Data & Artificial Intelligence Authority (SDAIA) Vision: Leading the Kingdom's Journey toward Global Leadership.
Journal of epidemiology and global health
Apr 8, 2021
The emerging field of data and artificial intelligence (AI) and its noticeable expansion has motivated nations to transition from traditional economic models to learning economies using these technologies. In April 2016, the Crown Prince Mohammed bin...
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