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Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data
A highly variable clinical course, immune dysfunction, and a complex genetic blueprint pose challenges for treatment decisions and the management of risk of infection in patients with chronic lymphocytic leukemia (CLL). In recent years, the use of machine learning (ML) technologies has made it possi...
Autores principales: | Parviz, Mehdi, Brieghel, Christian, Agius, Rudi, Niemann, Carsten U. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Hematology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9631547/ https://www.ncbi.nlm.nih.gov/pubmed/35468622 http://dx.doi.org/10.1182/bloodadvances.2021006351 |
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