Get films read
A licensed radiologist’s signed report, in Dari or Pashto, returned over the channel clinics already use — WhatsApp — typically within the hour. Access and turnaround, where before there was no reader at all.
Across Afghanistan, clinics own working X-ray machines and have no radiologist to read the films — for a child’s fractured arm as much as for a tuberculosis screen. Partaw Research works to close that reading gap as a public good, and to build the missing evidence base while doing it.
≈ 100
radiologists per million people in high-income countries
Fewer than 2
radiologists per million people in low-income countries
Two-thirds
of the world’s population lacks access to basic diagnostic radiology. 1
About an hour
typical time from a clinic’s WhatsApp photo of a film to a signed report, on the platform we study.
One signature
no report reaches a clinic without a licensed radiologist’s name and license number on it. That rule lives in the platform’s code, not in a policy document.
An X-ray is only as useful as its reading. Decades of aid and procurement have put working machines into district clinics and provincial hospitals; the training pipelines that produce people qualified to read the output have not kept pace, and the few specialists there are concentrate in the largest cities. So films wait, travel with relatives to Kabul, or go unread — and the fracture is set blind, the pneumonia is treated on guesswork, the tuberculosis walks back out the door.
This is what we mean by radiology access as a public good: the reading, not the machine, is the scarce resource. It can be delivered over infrastructure clinics already hold in their hands — a smartphone and a WhatsApp thread — by a licensed radiologist who may be anywhere, with a signature and a verification code that make the report worth trusting.
A licensed radiologist’s signed report, in Dari or Pashto, returned over the channel clinics already use — WhatsApp — typically within the hour. Access and turnaround, where before there was no reader at all.
Teleradiology in this setting is barely described in the literature. We run programs as studies — protocols, outcomes, and publications with academic partners — so the model can be judged, improved, and reused.
Consented, de-identified reads accumulate into a research corpus of rural Afghan radiology — a population nearly absent from the datasets modern imaging is built on.
Each program aims the reading pathway at one clinical need, with its own partners, protocols, and dataset. The first and deepest is tuberculosis case-finding — Afghanistan carries a heavy TB burden2, and chest X-ray screening is where unread films cost the most.
Active Flagship program
WHO-recommended CAD triage paired with human radiologists — the architecture, its limits, and the study, written to be sent to a TB-ecosystem partner on its own.
Read the program
Candidates What comes next
The reading gap is not a TB problem — it swallows fractures, pneumonias, and children’s films just the same. Each candidate area launches when its partners and funders exist.
See the index
Rural and peri-urban Afghan radiology, photographed from real films on real phones in a conflict-affected, high-burden setting — a population and an image modality nearly absent from the corpora that imaging research and imaging AI are built on. It accumulates read by read.
Research & partnershipsConsented at intake, before a film enters any research use.
De-identified at the platform boundary, before research use.
Shared under data-governance agreements. Never sold.
We are looking for academic radiology and global-health programs, imaging-AI teams, and TB-ecosystem NGOs and funders. What is on offer — authorship, advisory seats, and a governed validation site — is laid out plainly on the research page.