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Then H H Patrick1, A Y Y Fong, Y Sebastian
1School of Computing and Design, Swinburne University of Technology, Sarawak, Malaysia. pthen@swinburne.edu.my
Informatics for Health & Social Care
|March 24, 2009
Summary
This study addresses challenges in medical data mining, particularly with diverse imaging modalities and vendor formats. Prototyping and user engagement were key to developing a practical data mining tool for medical applications.
Area of Science:
- Medical Informatics
- Data Science
- Medical Imaging
Background:
- Medical data mining faces significant hurdles due to diverse imaging modalities and varying equipment formats from different vendors.
- User adoption is a challenge, as medical professionals' interest and engagement are crucial for developing practical data mining tools for diagnosis and planning.
Purpose of the Study:
- To overcome challenges in medical data mining, focusing on data integration, compatibility, and user engagement.
- To develop and validate a practical data mining tool for medical applications by involving end-users throughout the development process.
Main Methods:
- Employed requirement engineering techniques, specifically prototyping, to enhance user engagement.
- Integrated data from various equipment and vendors to facilitate efficient data analysis, charting, and reporting.
Main Results:
- Successfully merged data from different equipment and vendors for comprehensive analysis.
- Demonstrated the practical utility and capability of the developed data miner to medical doctors through prototype walkthroughs.
Conclusions:
- Prototyping and user-centered design are effective in overcoming challenges in medical data mining tool development.
- The developed data mining tool shows promise for enhancing medical diagnosis and planning processes by integrating diverse data sources.
