scholarly journals An improved predictive association rule based classifier using gain ratio and T-test for health care data diagnosis

Sadhana ◽  
2015 ◽  
Vol 40 (6) ◽  
pp. 1683-1699 ◽  
Author(s):  
M NANDHINI ◽  
S N SIVANANDAM
Keyword(s):  
Health Care ◽  
Association Rule ◽  
T Test ◽  
Rule Based ◽  
Gain Ratio ◽  
Health Care Data ◽  
Rule Based Classifier

Privacy Preserving Integration of Health Care Data

2012 ◽  
pp. 94-107 ◽  
Author(s):  
Xiaoyun He ◽  
Jaideep Vaidya ◽  
Basit Shafiq ◽  
Nabil Adam ◽  
Tom White
Keyword(s):  
Health Care ◽  
Data Integration ◽  
Privacy Preserving ◽  
Cross Linking ◽  
Health Care Information ◽  
Multiple Sources ◽  
Rule Based ◽  
Related Research ◽  
Health Care Data ◽  
Care Information

For health care related research studies the medical records of patients may need to be retrieved from multiple sites with different regulations on the disclosure of health information. Given the sensitive nature of health care information, privacy is a major concern when patients’ health care data is used for research purposes. In this paper, the authors propose approaches for integration and querying of health care data from multiple sources in a secure and privacy preserving manner. In particular, the first approach ensures secure data integration based on unique identifiers, and the second one considers data integration based on quasi identifiers, for which a rule-based framework is proposed for cross-linking data records, including secure character matching.

Privacy Preserving Integration of Health Care Data

2010 ◽  
Vol 1 (2) ◽  
pp. 22-36 ◽  
Author(s):  
Xiaoyun He ◽  
Jaideep Vaidya ◽  
Basit Shafiq ◽  
Nabil Adam ◽  
Tom White
Keyword(s):  
Health Care ◽  
Data Integration ◽  
Medical Records ◽  
Information Privacy ◽  
Privacy Preserving ◽  
Health Care Information ◽  
Multiple Sources ◽  
Rule Based ◽  
Health Care Data ◽  
Care Information

For health care related research studies the medical records of patients may need to be retrieved from multiple sites with different regulations on the disclosure of health information. Given the sensitive nature of health care information, privacy is a major concern when patients’ health care data is used for research purposes. In this paper, the authors propose approaches for integration and querying of health care data from multiple sources in a secure and privacy preserving manner. In particular, the first approach ensures secure data integration based on unique identifiers, and the second one considers data integration based on quasi identifiers, for which a rule-based framework is proposed for cross-linking data records, including secure character matching.

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