A geno-clinical decision model for the diagnosis of myelodysplastic syndromes.
Blood Adv
; 5(21): 4361-4369, 2021 11 09.
Article
en En
| MEDLINE
| ID: mdl-34592765
ABSTRACT
The differential diagnosis of myeloid malignancies is challenging and subject to interobserver variability. We used clinical and next-generation sequencing (NGS) data to develop a machine learning model for the diagnosis of myeloid malignancies independent of bone marrow biopsy data based on a 3-institution, international cohort of patients. The model achieves high performance, with model interpretations indicating that it relies on factors similar to those used by clinicians. In addition, we describe associations between NGS findings and clinically important phenotypes and introduce the use of machine learning algorithms to elucidate clinicogenomic relationships.
Texto completo:
1
Colección:
01-internacional
Asunto principal:
Síndromes Mielodisplásicos
/
Trastornos Mieloproliferativos
Tipo de estudio:
Diagnostic_studies
/
Health_economic_evaluation
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Blood Adv
Año:
2021
Tipo del documento:
Article