Paul Heider, Stéphane Meystre J Med Internet Res 2024;26:e55676, doi: 10.2196/55676, PMID: 38805692 Available at: https://www.jmir.org/2024/1/e55676
Our paper on “A Comparative Analysis of Speed and Accuracy for Three Off-the-Shelf De-Identification Tools” has been awarded the Data Science Best Paper Award at the AMIA 2020 Informatics Summit.
Our interactive panel at the AMIA annual symposium encountered great success and active participation by the audience. The audience experience with automatic text de-identification we limited, based on their feed-back: Presenters included...
Kim, Y., Heider, P., & Meystre, S. M. (2018). Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives. AMIA Annu Symp Proc. 663–672.
The U.S. Veterans Healthcare Administration (VHA) Consortium for Healthcare Informatics Research (CHIR) is a multi-disciplinary group of collaborating investigators affiliated with VHA sites across the U.S. In the context of the CHIR, this...