Supplementary Information from A Machine Learning–Based Strategy Predicts Selective and Synergistic Drug Combinations for Relapsed Acute Myeloid Leukemia

Key Points

• 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.