In this first episode of Pixels 2 Patients, I’m joined by Max Ilse, Senior Researcher at Microsoft Health Futures, to discuss his latest paper, Data Scaling Laws for Radiology Foundation Models (arXiv:2509.12818).

We dive into the core findings of his research, exploring how scaling laws, long studied in natural language processing and vision, apply to the medical imaging domain. We talk about the trade-offs between building large, generalist models that perform across many tasks versus developing highly specialised models that excel within a particular population or modality.

Max also shares his thoughts on the current bottlenecks facing radiology foundation models, underexplored areas of research ...