Genomic Classification of Acute Lymphoblastic Leukemia Using AI: Towards Personalized Medicine

Abstract excerpt

Acute lymphoblastic leukemia is a highly heterogeneous hematologic malignancy that poses significant challenges for clinicians in terms of early detection and accurate subtype classification. Misclassification or delayed recognition of molecular subtypes can lead to suboptimal treatment decisions and negatively impact patient outcomes. Traditional diagnostic methods, while effective, often lack the sensitivity to...

Topics

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• Acute Lymphoblastic Leukemia research
• Acute Myeloid Leukemia Research
• AI in cancer detection
• Cancer Genomics and Diagnostics
• Gene expression and cancer classification
• Myeloproliferative Neoplasms: Diagnosis and Treatment
• Radiomics and Machine Learning in Medical Imaging

Identifiers and source

Literature Corpus work

9be8ad76-e473-5992-9f7e-1e43f848d056

DOI

10.1101/2025.09.20.25336225