Automated clinical text anonymization has the potential to unlock the widespread sharing of
textual health data for secondary usage while assuring patient privacy and safety. Despite …

The growing number of cases indicates that large language model (LLM) brings
transformative advancements while raising privacy concerns. Despite promising recent …

This study addresses privacy concerns in real-time streaming data, including personal
biometric signals and private information from sources such as real-time crime reporting …

Text sanitization is the task of redacting a document to mask all occurrences of (direct or
indirect) personal identifiers, with the goal of concealing the identity of the individual (s) …

Anonymization of clinical text is crucial to allow the sharing and disclosure of health records
while safeguarding patient privacy. However, automated anonymization processes are still …

Responsible natural language processing is more and more concerned with preventing the
violation of personal rights that language technology can entail (CITATION). In this paper we …

Text sanitization is the task of detecting and removing personal information from the text.
While it has been well-studied in monolingual settings, today, there is also a need for …

Abstract Integrating Artificial Intelligence (AI) in clinical Decision Support Systems (DSS) can
significantly transform healthcare in many ways to improve patient outcomes. Despite these …