Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence
Most Cited Paper
in Acute Myeloid Leukemia Research
18 Months Post-Publication
Class of 2026
“Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence”
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Topics
synthetic data generation · Acute myeloid leukemia (AML) · generative artificial intelligence · CTAB-GAN+ · normalizing flows · synthetic control cohorts · multimodal clinical data · survival analysis · patient re-identification · Hamming distances · molecular variables · cytogenetic variables · Multicenter clinical trial · rare diseases · data privacy · Data fidelity · usability metrics · univariable outcome analysis · inter-variable relationships
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Pepkio Research Index (PRI). Topics and Trends in Most Cited Acute Myeloid Leukemia Research Papers, Class of 2026. https://pri.pepkio.com/top-papers/acute-myeloid-leukemia-research/2026. Accessed 2026-07-31. Methodology Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459