Privacy Enhanced Healthcare Data Management Using Associative Data Mining Approaches

Abstract Hospital medical records with health examination findings can be integrated to assist in uncovering the link between aberrant test results and illness. It is possible to establish a disease-preventive knowledge center using these integrated data by performing associated rule mining on the results. In order to integrate data, sensitive patient information must be shared. Patients’ privacy may be violated by the disclosure of sensitive information. Thus, privacy-preserving associated rule mining in physically partitioned healthcare data is addressed in this article. The suggested technique is further evaluated in terms of data protection, transmission, and computing costs.