Naveen Kumar Parachur Cotha

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Our study considers identification of demographic attributes of patients as a multi-label learning problem. This is a novel approach to predict accuracy of classification of patients’ quasi-identifiers (race and gender attributes). To classify the sets of attributes, we applied ensembles of several multi-label learning algorithms. The best-performing(More)
Automated learning of patients’ demographics can be seen as multilabel problem where a patient model is based on different race and gender groups. The resulting model can be further integrated into Privacy-Preserving Data Mining, where they can be used to assess risk of identification of different patient groups. Our project considers relations between(More)
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