Prediction of Lymphoma Aggressiveness Using Machine Learning Algorithms
LNC, FC, and other rapidly available parameters are associated with the aggressive nature of the lymphomas. It is possible to combine them in multivariable models to obtain a valuable diagnostic information and to initiate a prompt treatment.
Authors
- François Mullier (ORCID: https://orcid.org/0000-0001-6947-6099)
- V. Lepage
- Carlos Graux (ORCID: https://orcid.org/0000-0001-9236-3623)
- Jonathan Degosserie (ORCID: https://orcid.org/0000-0001-8654-4831)
- Caroline Fervaille
- Julien Cabo (ORCID: https://orcid.org/0000-0001-5630-7114)
- Nicolas Debortoli (ORCID: https://orcid.org/0000-0002-1145-9146)
- Reza Soleimani (ORCID: https://orcid.org/0000-0002-9925-4566)
- Benoît Bihin (ORCID: https://orcid.org/0000-0002-8713-6319)
- Marie Pouplard
- R Bennis
- Thierry Vander Borght
- Julien Favressed
Institutions
- University of Namur (BE)
- Namur Research Institute for Life Sciences
- UCLouvain (BE)
Publication Details
- Journal
- International Journal of Laboratory Hematology
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1111/ijlh.14474
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00