A geno-clinical decision model for the diagnosis of myelodysplastic syndromes.
Blood Adv
; 5(21): 4361-4369, 2021 11 09.
Article
em 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
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Síndromes Mielodisplásicas
/
Transtornos Mieloproliferativos
Tipo de estudo:
Diagnostic_studies
/
Health_economic_evaluation
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article