Lower back pain is the most common musculoskeletal issue in the U.S. and a top cause of global disability. To tackle this, researchers have developed a groundbreaking AI-powered system that automates patient-specific lumbar spine modeling. By merging deep learning with biomechanical simulation, the new method slashes model prep time by nearly 98% – from more than 24 hours to just 30 minutes – while preserving clinical accuracy. This innovation enables faster, more consistent diagnoses and personalized treatment planning.

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.