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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File: | <div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Chong ITMWebConf21 36.png|240px]]</div> | ||
'''"[[Journal: | '''"[[Journal:Privacy-preserving healthcare informatics: A review|Privacy-preserving healthcare informatics: A review]]"''' | ||
The [[electronic health record]] (EHR) is the key to an efficient healthcare service delivery system. The publication of healthcare data is highly beneficial to healthcare industries and government institutions to support a variety of medical and census research. However, healthcare data contains sensitive [[information]] of patients, and the publication of such data could lead to unintended [[Information privacy|privacy]] disclosures. In this paper, we present a comprehensive survey of the state-of-the-art privacy-enhancing methods that ensure a secure healthcare [[data sharing]] environment. We focus on the recently proposed schemes based on data anonymization and differential privacy approaches in the protection of healthcare data privacy. We highlight the strengths and limitations of the two approaches and discuss some promising future research directions in this area. ('''[[Journal:Privacy-preserving healthcare informatics: A review|Full article...]]''')<br /> | |||
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Revision as of 16:14, 31 January 2022
"Privacy-preserving healthcare informatics: A review"
The electronic health record (EHR) is the key to an efficient healthcare service delivery system. The publication of healthcare data is highly beneficial to healthcare industries and government institutions to support a variety of medical and census research. However, healthcare data contains sensitive information of patients, and the publication of such data could lead to unintended privacy disclosures. In this paper, we present a comprehensive survey of the state-of-the-art privacy-enhancing methods that ensure a secure healthcare data sharing environment. We focus on the recently proposed schemes based on data anonymization and differential privacy approaches in the protection of healthcare data privacy. We highlight the strengths and limitations of the two approaches and discuss some promising future research directions in this area. (Full article...)
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