Multimodal identification of a rare head and neck cancer patient cohort in the clinical data warehouse of Greater Paris Teaching Hospital
This study demonstrates the feasibility and utility of a multimodal electronic health record-based approach to identify rare HNC patients in a CDW. Incorporating free-text and structured data improves the reliability of such cohort identification.
Authors
- B. Baujat (ORCID: https://orcid.org/0000-0003-3930-3191)
- Ambre La Rosa (ORCID: https://orcid.org/0000-0002-3704-9970)
- Xavier Tannier (ORCID: https://orcid.org/0000-0002-2452-8868)
- Sarah Atallah (ORCID: https://orcid.org/0000-0001-8702-1119)
- Emmanuelle Kempf (ORCID: https://orcid.org/0000-0002-9285-1966)
- Ilaria Lolli (ORCID: https://orcid.org/0000-0003-0023-0781)
- M. Verdoux
- Christel Daniel (ORCID: https://orcid.org/0000-0001-7938-8156)
- Pierre Riebler (ORCID: https://orcid.org/0009-0008-3118-2317)
Institutions
- Inserm (FR)
- Université Paris-Est Créteil (FR)
- Université Paris-Saclay (FR)
- Centre Hospitalier Universitaire Henri-Mondor (FR)
- Sorbonne Université (FR)
- Sorbonne Paris Cité (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Hôpitaux Universitaires Henri-Mondor (FR)
- Bicêtre Hospital (FR)
- Hôpital Tenon (FR)
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé
- Université Paris 1 Panthéon-Sorbonne (FR)
Publication Details
- Journal
- ESMO Real World Data and Digital Oncology
- Published
- 2025-05-29
- DOI
- https://doi.org/10.1016/j.esmorw.2025.100151
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00