Bright

BRIGHT EVIDENCE PACK / Emerging

Twelve millimetres, or three centimetres.

A breast cancer found by imaging is typically about 12 mm across. One found by a hand — a woman's own, or a clinician's — is typically about 21 mm. In India, where almost no one is screened, four out of five recorded tumours are already 3 cm or larger when they are found.

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Dates and assessment

Source published
2025-12-11
Bright published
2026-09-09
Substantive update
2026-09-12
Evidence state
Emerging
Independent verification
Not established by this source review
Last source review
2026-09-12

The claim in context

The human problem

India has no organised breast screening programme. In NFHS-5, 0.9% of women aged 30 to 49 had ever had a clinical breast examination. The cancer is found late because nobody is looking early.

The prior constraint

Mammography needs a machine, a building and a radiologist. Rural districts have none of the three within reach, and a screening programme creates more images than the available radiologists can read.

AI’s actual role

MedCognetics' cleared software does one narrow thing: it flags an exam so that suspicious studies rise in the radiologist's reading queue. FDA cleared it for triage and worklist prioritization only. It does not mark lesions, does not remove a study from the queue, and must not be relied on to make or confirm a diagnosis. A radiologist still reads everything.

The documented result

MedCognetics holds two FDA 510(k) clearances for mammography triage: K220080, cleared 29 September 2022, and K252482, cleared 11 December 2025. NVIDIA reported in October 2025 that the software runs on mobile screening vans operated by Health Within Reach in India, and that more than 3,500 women had been screened; that account is the companies' own.

Why it may matter

Access, not cleverness, is the whole of this story. A van that reaches a district where 0.9% of women have ever been examined changes what stage the disease is found at — and stage is most of what survival depends on.

Limitations

Original evidence

Attribution

Credit Bright AI Future and link the canonical Bright record.

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