Our research (Generative Adversarial Networks-Driven Synthetic Patient Data Creation for Risk Identification in Childhood Acute Lymphoblastic Leukemia), which builds upon our previous work using Graph Neural Networks (GNN) for the 6-MP drug and provides a leukemia risk classification mechanism with synthetic patients obtained using Generative Adversarial Networks (GAN), was presented at the International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) 2025 on November 15, 2025!
The study will soon be indexed in the IEEE Xplore database.
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