Step 1
Patients contribute data
Imaging, labs, medications, and records are added to a patient-controlled account.
VisitVizor
Loading your workspace
Preparing your dashboard, records, and imaging tools.
VisitVizor
Preparing your dashboard, records, and imaging tools.
VisitVizor LEAD Research Initiative
Longitudinal Evidence & Discovery
Clinical trials for diseases like cancer may include
only 100–200 patients
But in the real world,
thousands — often millions —
are treated
Their imaging, labs, medications, and outcomes exist — but they are scattered across:
CDs
paper records
disconnected systems
individual providers
Massive amounts of real-world medical data go completely unused.
Most care delivery systems are optimized for treating patients, not for building longitudinal research datasets over time.
Even when imaging, labs, medications, and outcomes exist, they stay fragmented across institutions, formats, and disconnected workflows.
Building that continuity manually is expensive and slow, so data that could answer real-world questions never becomes research-ready at scale.
So even when the data exists, it is rarely usable for large-scale discovery.
VisitVizor enables patients to contribute their own medical data - including imaging, labs, medications, and records - into a unified, longitudinal dataset.
Instead of trying to build this dataset from the top down, it is built from the patient outward.
Patients become part of the solution.
Privacy and Trust
Data contributed to the LEAD Initiative is structured and de-identified.
Records are tied together longitudinally - across imaging, labs, medications, and outcomes - but not back to personally identifiable information.
This allows:
while maintaining confidentiality.
Where appropriate, limited attributes such as age range or gender can be included to support valid research without exposing identity.
When longitudinal, multimodal data exists at scale, entirely new questions can be answered:
Patients who respond well to treatment might share common factors we haven't thought of or seen before - but those patterns are rarely captured across populations.
The same is true for:
Not because the data does not exist - but because it has never been collected, connected, and studied at scale.
Until now.
Step 1
Imaging, labs, medications, and records are added to a patient-controlled account.
Step 2
Information is organized into a longitudinal medical history.
Step 3
Personal identity is removed while preserving analytical value.
Step 4
Qualified researchers work with large-scale, real-world datasets to generate findings.
Medicine advances when we understand what actually works - across real patients, over time.
The LEAD Research Initiative makes that possible by turning everyday patient data into large-scale clinical insight.