De-identification techniques to preserve privacy in medical records
Rosario Catelli and Massimo Esposito, Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), Naples, Italy
Abstract
The COVID-19 pandemic has required a collective global effort to be faced. The need to rapidly exchange clinical information to advance medical investigations has highlighted the importance of clinical de-identification techniques to make protected health information in electronic health records shareable and publishable while fully complying with privacy regulations. In this study, a comparative analysis is provided regarding the performance of language models with respect to the Italian language, employing ...
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