Article

Towards the Gene Profile of Acute Myeloid Leukaemia Using Machine Learning and Blood Transcriptomics

2024-02-12

Abstract excerpt

Applying the iterative methodology for dimensionality reduction/feature selection using categorical gradient boosted trees, as it has been defined in and has been successfully applied on similar datasets in and , on a dataset consisted of 12708 gene expressions coming from 5052 individuals from 105 studies, we classify whether a person has acute myeloid leukaemia (AML) or is healthy. A CatBoost model on a dataset...

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Literature Corpus work: 7b12baea-4f4d-5eea-9c5e-5bb95c67c8f0
DOI: 10.20944/preprints202402.0593.v1

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