PIDgeon: An Explainable AI Model for Improved Flow Cytometry-Based Screening of Lymphoid Primary Immunodeficiencies
In summary, PIDgeon is an accessible and explainable AI-pipeline aligned with current clinical needs, aiding laboratory immunologists in early PID diagnostics and increasing data analysis efficiency.
Authors
- Jacques J. M. van Dongen (ORCID: https://orcid.org/0000-0002-3650-7087)
- Annelies Emmaneel (ORCID: https://orcid.org/0000-0003-4569-2330)
- Mattias Hofmans (ORCID: https://orcid.org/0000-0003-2061-7617)
- Jana Neirinck (ORCID: https://orcid.org/0000-0002-0084-9245)
- Ciel De Vriendt (ORCID: https://orcid.org/0000-0002-5213-5391)
- Sarah Bonte (ORCID: https://orcid.org/0000-0002-0637-4893)
- Tessa Kerre
- Mirjam van der Burg
- Tomáš Kalina
- Yvan Saeys (ORCID: https://orcid.org/0000-0002-0415-1506)
- Carolien Bonroy
- Martín Pérez-Andrés
- Malicorne Buysse
- Alba Torres-Valle
- Alberto Orfao
- Sofie Van Gassen
- Bart N Lambrecht
Institutions
- HOGENT University of Applied Sciences and Arts (BE)
- Universidad de Salamanca (ES)
- Charles University (CZ)
- Leiden University Medical Center (NL)
- Ghent University Hospital (BE)
- Instituto de Salud Carlos III (ES)
- Ghent University (BE)
- Instituto de Investigación Biomédica de Salamanca (ES)
- Centro de Investigación del Cáncer (ES)
- VIB-UGent Center for Inflammation Research (BE)
- Medical Research Network (US)
Publication Details
- Journal
- Clinical Chemistry
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1093/clinchem/hvaf190
- Primary Topic
- Immunodeficiency and Autoimmune Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00