Abstract
A privacy-preserving patient-centric clinical decision support system, called PPCD, is based on naive Bayesian classification to help the physician predict disease risks of patients in a privacy-preserving way. First, the authors propose a secure PPCD, which allows the service providers to diagnose a patient's disease without leaking any patient medical data. In PPCD, the past patient's historical medical data can be used by a service provider to train the naive Bayesian classifier. Then, the service provider can use the trained classifier to diagnose a patient's diseases according to his symptoms in a privacy-preserving way. Finally, patients can retrieve the diagnosed results according to their own preference privately without compromising the service provider's privacy.
Published Version
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