Ontology highlight
ABSTRACT:
SUBMITTER: Radakovich N
PROVIDER: S-EPMC8579270 | biostudies-literature | 2021 Nov
REPOSITORIES: biostudies-literature
Radakovich Nathan N Meggendorfer Manja M Malcovati Luca L Hilton C Beau CB Sekeres Mikkael A MA Shreve Jacob J Rouphail Yazan Y Walter Wencke W Hutter Stephan S Galli Anna A Pozzi Sara S Elena Chiara C Padron Eric E Savona Michael R MR Gerds Aaron T AT Mukherjee Sudipto S Nagata Yasunobu Y Komrokji Rami S RS Jha Babal K BK Haferlach Claudia C Maciejewski Jaroslaw P JP Haferlach Torsten T Nazha Aziz A
Blood advances 20211101 21
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 de ...[more]