Supplementary Information from A Machine Learning–Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia | Synapse
August 4, 2025
Supplementary Information from A Machine Learning–Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia
Puntos clave
MAIN FINDING: Machine learning effectively predicts selective drug combinations for acute myeloid leukemia.
KEY EVIDENCE: The model identifies synergistic pairs of drugs that enhance treatment efficacy in relapsed cases.
APPROACH: Analysis involved a machine learning strategy utilizing various drug data and disease outcomes.
SIGNIFICANCE: This approach could revolutionize treatment personalization for patients with relapsed acute myeloid leukemia.