A quantum generative model for in silico clinical trials using scarce training datasets

In silico methods have emerged as a strategy to complement clinical trials. These are particularly relevant for rare or heterogeneous diseases for which traditional methods are costly or difficult to apply. While classical generative models have shown an extremely good ability to generate high fidel