For the first time, researchers show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia (AML). Their proof of concept study paves the way for an automated, standardized and on-hand sample analysis in the near future.

What does a simulation tell us? It's a question asked across many fields, such as epidemiology and climate science. Probabilistic programming offers a solution –essentially reverse-engineering the simulation – but this is a complex, computing power-heavy technique. A new project, capable of controlling existing simulators and running at large-scale on HPC platforms, could revolutionize the field.