Open Access Opinion

Efficacy of Weka for Medical Data Mining: Ambulatory Blood Pressure Monitoring as A Case-Study

Chuiko GP1*, Darnapuk YS2, Dvormik OV3, Honcharov DA4 and Yaremchuk OM5

1Professor, Department Computer Engineering, Ukraine

2Senior Lecturer, Department Computer Engineering, Ukraine

3Associate Professor, Department Computer Engineering, Ukraine

4Head of Lab, Information Computer Center, Ukraine

5Professor, Dean of Medical Institute, Ukraine

Corresponding Author

Received Date: April 24, 2023;  Published Date: May 11, 2023

Ambulatory blood pressure monitoring (ABPM) gradually gained weight from the early 1960s. ABPM, alias 24-hour blood pressure trial, is one routine medical test for diagnosing and prophylactics of circulation upsets, particularly hypertension, even disguised [1]. Many medical databases exist concerning ABPM, sometimes quite detailed and ponderous enough, like [2]. Medical databases can comprise dozens and hundreds of various attributes, hundreds and even thousands of instances. Detalization makes such datasets rich on the one hand but just “big data” on the other. “Big data” scares clinicians, who are primarily unfamiliar with modern data mining means. One innovative solution is comprehensive visualization and graphical user interface (GUI) for medical data mining tools.

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