Prediction of bone marrow fibrosis from complete blood count in myeloproliferative neoplasms (FIBOM-AI): a multicentre machine learning model development and validation study

The Lancet Haematology 2026

View at publisher
Authors: Marie Donzel, Syrine KHEDIMALLAH, Sabrina Barriere, Agathe Gouband, Christopher Aubert, Nelly Bosselut, Elsa Poullot, Silvia Maria Bezsera, Olivier Mansier, Nursemin Yilmaz, Charlotte Syrykh, Xavier Hittinger
+31 more Seddig MOMENKHAN, Fiorenza Barraco, Lila Gilis, Hélène Labussière-Wallet, Mathias Brehon, Benjamin Chin-Yee, Cyrus Hsia, Luojun Wang, Sarah Zouaghi, Pierre Sujobert, Marion Eveillard, Véronique De Mas, Suzanne Tavitian, Laurence Legros, Marie Parrens, Pascale Flandrin‐Gresta, Mathieu Meunier, Nicolas Freynet, Lydia Roy, Véronique Meignin, Louis Drevon, Dana Ranta, Simona Pagliuca, Éric Lippert, Jean‐Christophe Ianotto, Laurent Jallades, Barbara Burroni, Damien Luque Paz, Alexandra Traverse‐Glehen, Simon Chevalier, Vincent Alcazer
DOI: 10.1016/s2352-3026(26)00099-2
Cited by: 1
References: 24

Fields of Study & Subjects

Myeloproliferative Neoplasms: Diagnosis and Treatment Digital Imaging for Blood Diseases Imbalanced Data Classification Techniques

Publication details

Journal / source
The Lancet Haematology
Publisher
Elsevier BV
Volume
13
Issue
6
Pages
e396–e407
Publication date
1 June 2026
Language
EN