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

Puntos clave

• Machine learning predicts selective drug combinations for relapsed acute myeloid leukemia.
• The approach reveals synergistic effects among various drug pairings, enhancing treatment efficacy.
• Data from supplementary results supports the method’s predictive capabilities with detailed analysis.
• This advancement could lead to personalized therapy strategies for patients with relapsed acute myeloid leukemia.