Natural language processing (NLP) systems have been developed to provide access to the
tremendous body of data and knowledge that is available in the biomedical domain in the …

Medical data is one of the most rewarding and yet most complicated data to analyze. How
can healthcare providers use modern data analytics tools and technologies to analyze and …

Motivation: Global gene expression profiling, both at the transcript level and at the protein
level, can be a valuable tool in the understanding of genes, biological networks, and cellular …

Abstract Background and Objective Retrieving meaningful information from high
dimensional dataset is an important and challenging task. Normally, medical dataset suffers …

BACKGROUND: The patient problem list is an important component of clinical medicine.
The problem list enables decision support and quality measurement, and evidence suggests …

Data mining (DM) is part of a process by which information or knowledge can be extracted
from data or databases and used to inform decision-making in a variety of contexts …

Microarray datasets typically contain large number of columns but small number of rows.
Association rules have been proved to be useful in analyzing such datasets. However, most …

In this paper, we propose a novel algorithm to discover the top-k covering rule groups for
each row of gene expression profiles. Several experiments on real bioinformatics datasets …

Currently, an automated methodology based on association rules is presented for the
detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The …

Objective Determine how varying longitudinal historical training data can impact prediction
of future clinical decisions. Estimate the “decay rate” of clinical data source relevance …