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Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions
20
Zitationen
8
Autoren
2024
Jahr
Abstract
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.
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Autoren
Institutionen
- Assistance Publique – Hôpitaux de Paris(FR)
- Sorbonne Université(FR)
- Institut Pierre Louis d‘Épidémiologie et de Santé Publique(FR)
- Inserm(FR)
- Bicêtre Hospital(FR)
- Université Paris Cité(FR)
- Université Sorbonne Paris Nord(FR)
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé
- Hôpital Albert-Chenevier(FR)