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However, the original intention of medical informatization is to improve medical efficiency and break the information barriers between medical institutions, which is also limited by genetic privacy risks from growing bioinformatics data. To share biomedical data correlated with genes usefully under the premise of ensuring genetic privacy, with the concept of medical reference interval, we design a query strategy based on a flexible differential privacy algorithm that setting weights for noise added according to the purpose of the inquirer. We generate a series of biomedical data to test the effectiveness of our query system, the test results show that our algorithm ensures data\u2019s utility with acceptable privacy breaches that addresses the problem of biomedical data sharing to a certain extent.<\/jats:p>","DOI":"10.1142\/s021812662250236x","type":"journal-article","created":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T10:23:06Z","timestamp":1651141386000},"source":"Crossref","is-referenced-by-count":2,"title":["Utility-Prioritized Differential Privacy for Quantitative Biomedical Data"],"prefix":"10.1142","volume":"31","author":[{"given":"Muqing","family":"He","sequence":"first","affiliation":[{"name":"Cluster and Grid Computing Lab, Services Computing Technology and System Lab, Big Data Technology and System Lab, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. 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