AIMC Topic: Data Mining
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Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.
Journal of medical systems
May 25, 2020
Coronaviruses (CoVs) are a large family of viruses that are common in many animal species, including camels, cattle, cats and bats. Animal CoVs, such as Middle East respiratory syndrome-CoV, severe acute respiratory syndrome (SARS)-CoV, and the new v...
Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas.
BioMed research international
May 18, 2020
BACKGROUND: Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find potential related genes for predicting the prognosis of patients with PRAD.
Neural networks for open and closed Literature-based Discovery.
PloS one
May 15, 2020
Literature-based Discovery (LBD) aims to discover new knowledge automatically from large collections of literature. Scientific literature is growing at an exponential rate, making it difficult for researchers to stay current in their discipline and e...
RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes.
International journal of radiation biology
May 12, 2020
Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins, ionizing water molecules to produce toxic free radicals, and triggering genetic and somatic effects. Understanding the biomolecular response mechani...
A review of modern technologies for tackling COVID-19 pandemic.
Diabetes & metabolic syndrome
May 7, 2020
OBJECTIVE: Science and technology sector constituting of data science, machine learning and artificial intelligence are contributing towards COVID-19. The aim of the present study is to discuss the various aspects of modern technology used to fight a...
Big Data and Atrial Fibrillation: Current Understanding and New Opportunities.
Journal of cardiovascular translational research
May 6, 2020
Atrial fibrillation (AF) is the most common arrhythmia with diverse etiology that remarkably relates to high morbidity and mortality. With the advancements in intensive clinical and basic research, the understanding of electrophysiological and pathop...
Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?
European radiology
May 6, 2020
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and c...
SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning.
Methods (San Diego, Calif.)
May 5, 2020
In recent years, accumulating studies have shown that long non-coding RNAs (lncRNAs) not only play an important role in the regulation of various biological processes but also are the foundation for understanding mechanisms of human diseases. Due to ...
Machine Learning Offers Exciting Potential for Predicting Postprocedural Outcomes: A Framework for Developing Random Forest Models in IR.
Journal of vascular and interventional radiology : JVIR
May 4, 2020
PURPOSE: To demonstrate that random forest models trained on a large national sample can accurately predict relevant outcomes and may ultimately contribute to future clinical decision support tools in IR.
Child, Preschool
Child
Hospital Mortality
United States
Length of Stay
Aged
Inpatients
Portasystemic Shunt, Transjugular Intrahepatic
Male
Adolescent
Retrospective Studies
Aged, 80 and over
Data Mining
Iatrogenic Disease
Time Factors
Middle Aged
Female
Pneumothorax
Young Adult
Radiography, Interventional
Humans
Risk Assessment
Infant, Newborn
Uterine Artery Embolization
Adult
Image-Guided Biopsy
Machine Learning
Infant
Risk Factors
Databases, Factual
The influence of preprocessing on text classification using a bag-of-words representation.
PloS one
May 1, 2020
Text classification (TC) is the task of automatically assigning documents to a fixed number of categories. TC is an important component in many text applications. Many of these applications perform preprocessing. There are different types of text pre...
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