Privacy-preserving machine learning
Developing AI that learns from clinical data without that data ever being exposed or leaving its source.
Trenthos Research builds privacy-preserving technology to improve how healthcare is delivered in Australia - with patient consent at the centre, and data that never leaves the country.
Much of the data and AI shaping healthcare today was built on overseas populations, in systems that move patient information far from the people it came from. Australian healthcare deserves better - locally relevant tools, developed responsibly, on infrastructure that stays on-shore.
Trenthos Research is our early-stage effort to close that gap. We are building the methods and infrastructure to advance healthcare AI without compromising the privacy of a single patient.
These are the directions we are building toward. We describe them honestly as research themes - areas we are actively working in, not capabilities we have already delivered.
Developing AI that learns from clinical data without that data ever being exposed or leaving its source.
Creating realistic, fully synthetic clinical data that can support research and software testing without using real patient records.
Building methods to train shared models across multiple sites so everyone benefits from better tools while each site's data stays on its own premises.
Turning routine, consented, de-identified clinical information into insight that can improve care and inform practice.
Exploring tools that help clinicians make faster, better-informed decisions at the point of care.
Researching how imaging - OCT, fundus photography and visual fields - might be analysed to surface useful signal for clinicians, always supporting rather than replacing their judgement.
These commitments come first, and everything we build is shaped by them. They are written to match the consent and privacy documents that govern how data is actually handled.
We write about the technical and regulatory realities of building healthcare technology in Australia - what works, what is harder than it looks, and what we are learning as we go.
Two hours of EHR for every hour with patients, 4,000 clicks a shift, an inbox that never empties. The evidence on documentation burden, and the workflow that answers it.
An AI scribe that only transcribes is not a medical device; one that diagnoses is. The TGA test that decides whether yours is regulated before launch.
The engineering underneath the word "compliant" - data residency, tenant isolation, audit, retention - and the Australian rules that decide the architecture.
Trenthos Research is founder-led and clinically informed. It is led by Dr Chun-Huei Liu, a clinically trained doctor building Trenthos and its first product, Lumen, with a focus on responsible health technology in Australia.
We are a small, growing team. We would rather say less and mean it than overstate where we are. As the work develops, this page will grow with it.
We are in the early stages, and actively interested in speaking with clinicians, researchers, and health services who share our view that better care and strong privacy are not in conflict. If that is you, we would like to hear from you.