In healthcare, we are not limited by what we know. We are limited by how we turn knowledge into systems that work in practice.
We generate more clinical knowledge than ever before. But most of it never reaches patients in a structured, scalable way.
The challenge is not discovery. It is how knowledge is implemented into real-world practice.
And AI and large language models may fundamentally change this. Not by replacing clinicians, but by enabling knowledge to be translated, scaled, and applied in practice.
Turning clinical data into validated, decision-ready knowledge.
Building clearer interfaces between specialist knowledge and public understanding.
Integrating models into practice rather than treating them as isolated tools.
Rethinking models of healthcare, including teleophthalmology and referral systems.