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Health Data Anonymization and Privacy

El Emam and Luk Arbuckle walk you through a risk-based methodology. Clinical data is valuable for research and other types of analytics. This book demonstrates techniques for handling different data types. Understand different methods for wor You just clipped your first slide!

Anonymizing Health Data

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    I am like this theory is a g I back there estimated. There are several variables to evaluate the anonymization level of a dataset. You can contact us , if you need further advices about data anonymization. For ethical and legal questions the Research Office is the main respondant.

    Special order items

    It provides several useful resources:. Skip to content Browse. Work with personal data Personal data is all information related to an identified or identifiable person. If a project involves personal data it is important to: Document the processes and the uses of the data data management plan, metadata, code used to process data, etc. Get valid consent of individuals.

    Cyber Security: Preserving Privacy Through Anonymization

    This consent must be given expressly in the case of processing of sensitive personal data. Inform participants on their personal data Anonymize data, as soon as the purpose of the processing permits Secure data against any violation Avoid transferring data abroad be sure to comply with the law if you want to do it Data anonymization Why data anonymization matters Data anonymization offers several advantages. In particular, it enables to: Prevent violations and missuse of the data Comply with legal obligations Publish the data Make data reusable Pseudonymization vs anonymization Pseudonymization: data directly identifying people names, ip addresses, phone number, etc.

    The key of the masked data is kept separately and securely.