In pancreatic cancer, knowing if there is metastasis is key to deciding whether to operate or not. Nowadays, a significant number of patients undergo unnecessary invasive surgeries because their metastasis was not detected in time.

"Our algorithm accurately predicts metastasis using images that are already routinely obtained," says Malats.

The article is published in the journal 'GUT'.

The algorithm will be tested in hospitals thanks to a project that has received nearly 800,000 euros in funding from the Spanish Department for Digital Transformation.

In Chaos, researchers in Istanbul develop a more efficient and flexible algorithm to model traffic. The model, which they call the data-driven macroscopic mobility model, relies on simple observations that city planners routinely collect, like how packed the streets are. The researchers tested their model on both synthetic benchmarks and real-world traffic data, and the faster simulation speeds and easier data requirements mean city planners may have the tools to design better, smarter cities.