Machine Learning for Multi-Omics Characterization of Blood Cancers: A Systematic Review.

ABSTRACT: Artificial Intelligence and machine learning are increasingly used to interrogate complex biological data. This systematic review evaluates their application to multi-omics for the molecular characterization of hematological malignancies, an area with unmet clinical need. We searched PubMed, Embase, Institute of Electrical and Electronics Engineers Xplore, and Web of Science from January 2015 to December 2024. Two reviewers screened records, extracted data, and used a modified appraisal emphasizing explainability, performance, reproducibility, and ethics. From 2847 records, 89 studies met inclusion criteria. Studies focused on acute myeloid leukemia (34), acute lymphoblastic leukemia (23), and multiple myeloma (18). Other hematological diseases were less frequently studied. Methods include

SUBMITTER: Alhamrani SQ 

PROVIDER: S-EPMC12427946 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature