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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
A user-oriented web crawler for selectively acquiring online content in e-health research
Songhua Xu1, Hong-Jun Yoon, Georgia Tourassi
1Biomedical Science and Engineering Center, Health Data Sciences Institute, Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN 37830, USA.
Bioinformatics (Oxford, England)
|October 1, 2013
Summary
This study introduces a user-oriented web crawler designed to efficiently gather online health data for researchers. The new adaptive web crawling technology significantly improves the accuracy and speed of acquiring relevant e-health information.
Area of Science:
- Health Informatics
- Computational Biology
- Data Science
Background:
- Vast amounts of patient and healthy individual data exist online, offering valuable insights into disease progression.
- Manual data collection via search engines is inefficient and incomplete for e-health research.
- Existing web crawling methods are often unaffordable or inefficient for targeted e-health data acquisition.
Purpose of the Study:
- To develop a user-oriented web crawler for adaptively acquiring specific online content for e-health research.
- To enhance the efficiency and relevance of online data collection for understanding patient health states.
Main Methods:
- Development of a user-oriented adaptive web crawler.
- Evaluation through two cancer-related case studies (breast and lung cancer).
- Comparison with state-of-the-art adaptive web crawling technology.
Main Results:
- The proposed crawler substantially accelerates the acquisition of highly relevant online content.
- Achieved significantly higher cumulative precision in breast and lung cancer case studies compared to a peer method.
- Demonstrated consistently superior accuracy in discovering and acquiring user-desired online content for e-health research.
Conclusions:
- The user-oriented web crawler effectively addresses the challenges of online data acquisition in e-health research.
- The developed crawler offers a more efficient and accurate solution for researchers seeking specific online health information.
- The implementation and datasets are available for non-commercial use.
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