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The Costs of Anonymization: Case Study Using Clinical Data
Privacy-enhancing technologies, including anonymization algorithms, can maintain the privacy of study participants when sharing data [10,11]. Anonymization reduces privacy risks by altering data in a manner such that it is highly unlikely that it can be related to a person. Anonymization can be performed using various transformation mechanisms, such as suppression, randomization, or generalization.
J Med Internet Res 2024;26:e49445
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Note that for some selected data sets and general anonymization problems, the World Bank Group, PARIS21 and Organization for Economic Cooperation and Development, and the International Household Survey Network supported the development of the anonymization software sdc Micro [7], and they all recommend it [8]. sdc Micro is actively used in many organizations, ranging from statistical offices [9] and social and political science [10] to the United Nations High Commissioner for Refugees [11] and health [12-14].
JMIR Public Health Surveill 2022;8(9):e34472
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The focus of this paper is to describe the SPHERE-CARED (Consent and Anonymization: A Review of Ethical Dimensions) study, exploring SPHERE participants’ perspectives on the ethical aspects of informed consent, anonymity, privacy, and data sharing. For a list of the SPHERE sensor technologies, including wearables, ambient sensors, and cameras, the interested reader should refer to the literature [8,17].
JMIR Mhealth Uhealth 2021;9(11):e25227
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Data Anonymization for Pervasive Health Care: Systematic Literature Mapping Study
This fact combined with the need for more accurate models in health care provides sufficient motivation for continued research into methods of data anonymization. For this study, we believe that how anonymization is defined is problem dependent. We reiterate that there is no clear-cut line between pseudonymization and anonymization because even anonymized data can practically have different reidentification risks [78,79] (depending on the type of anonymization performed).
JMIR Med Inform 2021;9(10):e29871
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However, given the increased sophistication of reidentification attacks [10-16] and the rising dimensionality (number of clinical and genetic attributes) of patient data, the above-mentioned countermeasures are inadequate to ensure a proper level of anonymization and preserve acceptable data utility. As a result, these conventional anonymization techniques for individual-level patient data are rarely used in practice.
J Med Internet Res 2021;23(2):e25120
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Hence, to address these concerns, anonymization studies and frameworks are currently being proposed for various datasets [8-10].
As CDM database research does not extract nor analyze the institutional raw data, it involves a low risk of personal information disclosure.
J Med Internet Res 2020;22(11):e19597
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Presence of the terms “de-identification” and “anonymization”
Definitions of the terms “de-identification” and “anonymization”
Meanings given to the terms “de-identification” and “anonymization”
Purposes of de-identification and anonymization
Limitations of the privacy-enhancing techniques
Ethical or legal considerations
Suggestions and recommendations
Data utility and information loss
Data sharing in biomedical research
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J Med Internet Res 2019;21(5):e13484
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