Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.
Thomas Petit-JeanChristel GérardinEmmanuelle BerthelotGilles ChatellierMarie FrankXavier TannierEmmanuelle KempfRomain BeyPublished in: Journal of the American Medical Informatics Association : JAMIA (2024)
We demonstrated that a community of investigators working on a common clinical data warehouse could efficiently and securely collaborate to develop, validate and use sensitive artificial intelligence models. In particular, we provided an efficient and robust NLP pipeline that detects conditions mentioned in clinical notes.