We are proud to announce the publication of “A decision support system to recommend appropriate therapy protocol for AML patients” in Frontiers in Artificial Intelligence [link]. This innovative research, conducted by Giovanna A. Castro, Jade M. Almeida, João A. Machado-Neto, and Tiago A. Almeida, introduces a machine learning-based decision support system designed to revolutionize treatment planning for Acute Myeloid Leukemia (AML) patients.
AML, one of the most aggressive hematological malignancies, requires timely and strategic treatment decisions. Existing risk classification systems face challenges in accurately assessing intermediate-risk patients, often leading to delays. This study addresses this critical issue by developing a robust system capable of recommending personalized therapy protocols with high precision.
Key findings of the study include:
- Achieving an F1-Score and AUC close to 0.9, demonstrating exceptional predictive accuracy.
- Superior performance when utilizing gene expression data for prognostic predictions.
- A significant impact on improving treatment decisions, patient survival, and quality of life.
This groundbreaking research highlights the potential of machine learning to optimize therapy planning and patient outcomes. The study was funded by CAPES, CNPq, and FAPESP, under grants 2021/11606-3 and 2021/13325-1. We extend our congratulations to the authors for their impactful contributions to oncology and artificial intelligence.