Predicting modelling for early diagnosis in early myeloproliferative neoplasms, not otherwise specified. Evidence from a machine learning study
This study represents a first step toward the development of automated tools to support MPN diagnosis, providing potential assistance to haematologists and pathologists in the clinical management of patients.
Authors
- Margherita Sonnessa
- Maria Colomba Comes (ORCID: https://orcid.org/0000-0003-2903-4389)
- Annarita Fanizzi (ORCID: https://orcid.org/0000-0002-2729-9896)
- Paolo Ditonno (ORCID: https://orcid.org/0000-0002-5187-7756)
- Anna Scattone (ORCID: https://orcid.org/0000-0001-6266-840X)
- Rossana Daprile
- Giuseppe Accogli (ORCID: https://orcid.org/0000-0003-4351-7395)
- Andrea Lupo
- Concetta Saponaro (ORCID: https://orcid.org/0000-0002-8196-3583)
- Samantha Bove (ORCID: https://orcid.org/0000-0001-7772-7513)
- Francesco Alfredo Zito
- Raffaella Massafra
Institutions
- Istituto Tumori Bari (IT)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2026-01-26
- DOI
- https://doi.org/10.3389/fonc.2025.1741610
- Primary Topic
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministero della Salute