This class is no longer accepting registrations
Data deidentification often poses a challenge to researchers. With more funders supporting or requiring data sharing, data deidentification is a crucial step in the data management lifecycle. This workshop will introduce and explore openly available tools and technologies to help with data deidentification.
Learn about artificial intelligence in the context of data deidentification and how technologies such as machine learning and natural language processing apply to deidentification.
We will focus on the NLM Scrubber from the National Library of Medicine and other open NLP tools that can be used for clinical text deidentification. Finally, explore ways to promote data privacy and data deidentification tools at your institution.
By registering for this class, you are agreeing to the NNLM Code of Conduct
This presentation addresses data and health information resources, as well as the NLM initiative of building a data-ready workforce by including information about deidentifying data and the NLM Scrubber resource.
1. Define artificial intelligence and natural language processing.
2. Compare NLM Scrubber and other clinical deidentification tools.
3. Implement open deidentification tools into library instruction and outreach programs.