Researchers at the University of Florida Health have developed an innovative AI-driven tool called the Acute Leukemia Methylome Atlas (ALMA) for the rapid diagnosis of acute leukemias, notably acute myeloid leukemia (AML). Published in Nature Communications, this open-access tool maps DNA methylation patterns from 3,300 leukemia samples, enabling efficient matching to 27 leukemia subtypes as per World Health Organization classifications. The atlas significantly reduces diagnostic wait times from weeks to just 2-3 days by leveraging an algorithm to compare new patient samples with existing data. Additionally, two AI tools predict patient outcomes, including five-year survival rates based on genetic markers. This technology enhances treatment decision-making and monitoring, aiming for wider access and improved remission rates globally. The research team plans clinical trials to refine ALMA further, including data collection on rare AML subtypes. This breakthrough promises to transform leukemia diagnostics and patient care significantly.
