# Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence

*PRI Rank #19 · Topics and Trends in Most Cited Acute Myeloid Leukemia Research Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/acute-myeloid-leukemia-research/2026/rank-19*

| Field | Value |
| --- | --- |
| Rank | #19 |
| 18m citations | 36 |
| Journal | npj Digital Medicine |
| Year | 2024 |
| DOI | 10.1038/s41746-024-01076-x |
| Corresponding authors | Jan‐Niklas Eckardt |
| Institution | Technical University Dresden, Germany |

**Ranking page:** [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)

**Paper link:** [10.1038/s41746-024-01076-x](https://doi.org/10.1038/s41746-024-01076-x)

## 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

## Cite this ranking

```
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.

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
```