Diagnostic Imaging Support
Explore what it would take to support a reporting clinician deciding which scan to read next, without creating an irresponsible stand-in dataset.
- Published sources
- 2
- Starter data
- None — by design
- Domain build partner
- build-diagnostic-imaging-support
- Last reviewed
From the draft strategy
Opportunity
The draft strategy names AI-based analysis of medical images as a potential public-service application: support for spotting fractures, cancers, and strokes in scans, with no clinical dataset or safety work attached to the suggestion.
Where the draft says it
Table 2 — potential public-service applications
Source register
Research already done
We reviewed these published sources so you do not have to start from zero. Each source shows what it covers, how it can be accessed, and why it matters.
2 sources
Department of Health
OpenDiagnostic waiting times
- What it covers
- How many people are waiting for a diagnostic test in Northern Ireland, how long they have waited, and how long reporting turnaround takes at each health and social care trust.
- Why it matters here
- It is the closest published figure to the pressure this example is meant to relieve, and it counts people and weeks rather than describing a single image.
Department of Health
OpenHospital waiting times statistics
- What it covers
- Quarterly outpatient, inpatient, diagnostic, and cancer waiting figures broken down by trust and by length of wait.
- Why it matters here
- It shows what is publicly available around imaging services and, by omission, that no image and no report ever leaves the clinical record.
Starter data
Starter dataset
No synthetic dataset — by design
Why we stopped
A scan cannot be honestly stood in for by a file of invented numbers, and every tabular stand-in we sketched for this task drifted towards describing individual patients rather than groups.
What responsible work needs instead
Anyone taking this further needs a partner radiology service and access to a real imaging archive under formal clinical-research governance, with a named sponsor, ethics approval, and reporting clinicians involved from the start.
Clone and build
Domain build partner
Build with a domain-aware coding agent
Clone the repository, then ask your coding agent to load the skill that ships with it. The skill brings the opportunity, sources, starter data, known unknowns and constraints into the conversation before anything is proposed. It follows the open Agent Skills standard, so it works in Claude Code, Codex and any other agent that reads skills.
01 / Clone
git clone https://github.com/Hypership-Software/lab-notes.ai.git02 / Invoke
- Claude Code
/build-diagnostic-imaging-support- Codex
$build-diagnostic-imaging-support
Conditions, not a checklist
Before you build
These are not footnotes. They are conditions that any responsible prototype would need to address.
Image errors change patient care
Missing a finding, or marking one that is not there, changes what happens to a patient, so nothing on this page should be read as a claim that image analysis is safe to use in care.
Published collections may not transfer
Openly published imaging collections come from other populations, other scanners, and other working practices, so how a system behaved on them says little about how it would behave here.
Visual support can misdirect attention
A confident outline drawn on a scan can pull a clinician's eye to the wrong place, which makes the support itself a source of harm rather than only a missed benefit.