Mining academic publications to automatically identify data sources

A Proposed Model to Identify Factors Affecting Asthma using Data Mining

Introduction: The identification of asthma risk factors plays an important role in the prevention of the asthma as well as reducing the severity of symptoms. Nowadays, the identification process can be performed using modern techniques. Data mining is one of the techniques which has many applications in the fields of diagnosis, prediction, and treatment. This study aimed to identify the effecti...

A Data Mining Approach To identify Diabetes

Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools provide a useful for alternative framework that addresses this problem. This study follows a DM technique to identify diabetic patients. We develop a model that clusters diabetes patients of a large healthcare company into different subpopulation. Consequently, we show the value of applying a DM ...

Automatically Integrating Life Science Data Sources

Data integration in the life sciences is currently implemented by very costly manually curated projects or by schemadriven approaches that require knowledge of the data sources and knowledge about schema integration techniques. We propose Aladin – an entirely different, almost automatic approach based on the database instances and domain knowledge on life science data sources. We focus on two m...

Using Meta-Data to Automatically Wrap BioInformatics Sources

Mining Multiple Large Data Sources

Effective data analysis using multiple databases requires highly accurate patterns. Local pattern analysis might extract low quality patterns from multiple large databases. Thus, it is necessary to improve mining multiple databases using local pattern analysis. We present existing specialized as well as generalized techniques for mining multiple large databases. We formalize the idea of multi-d...