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GBThe GuardianWomen's health

AI can detect heart disease in women using mammograms, study suggests

Experts say findings mean breast screenings for cancer could also flag cardiovascular problems in women Doctors have discovered a way to use routine mammograms that screen for breast cancer to spot heart disease, the world’s leading – and frequently underdiagnosed – cause of death in women. Researchers analysed the scans using artificial intelligence and were able to successfully identify women with coronary heart di

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Ledger record
#3508
First seen
27 Aug 2026, 14:16 UTC
Last checked
27 Aug 2026, 19:57 UTC
Version history
2 versions
Current fingerprint
57eca7be713b...e9b489
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Publisher layer

Recorded article metadata

Publisher
The Guardian
Country
England / United Kingdom
Source published
27 Aug 2026, 14:00 UTC
Source updated
No update timestamp supplied
Byline
Andrew Gregory Health editor in Munich
Section
Women's health
Source-supplied excerpt
Experts say findings mean breast screenings for cancer could also flag cardiovascular problems in women Doctors have discovered a way to use routine mammograms that screen for breast cancer to spot heart disease, the world’s leading – and frequently underdiagnosed – cause of death in women. Researchers analysed the scans using artificial intelligence and were able to successfully identify women with coronary heart di
02

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Observed version timeline

  1. 2
    Revision observed

    AI can detect heart disease in women using mammograms, study suggests

    Experts say findings mean breast screenings for cancer could also flag cardiovascular problems in women Doctors have discovered a way to use routine mammograms that screen for breast cancer to spot heart disease, the world’s leading – and frequently underdiagnosed – cause of death in women. Researchers analysed the scans using artificial intelligence and were able to successfully identify women with coronary heart di

    Changed fieldsdescriptionTextcontentText
    Version SHA-256
    57eca7be713b...e9b489
    Capture SHA-256
    71de68439176...29eb06
  2. 1
    Initial capture

    AI can detect heart disease in women using mammograms, study suggests

    Experts say findings mean breast screenings for cancer could also flag cardiovascular problems in women Doctors have discovered a way to use routine mammograms that screen for breast cancer to spot heart disease, the world’s leading and frequently underdiagnosed and cause of death in women. Researchers analysed the scans using artificial intelligence and were able to successfully identify women with coronary heart di

    Changed fieldstitlebylinedescriptionTextcontentTextsourcePublishedAtsourceUpdatedAtsectionimageUrltags
    Version SHA-256
    35b7df8c25aa...029be3
    Capture SHA-256
    a477d721ed10...c5b95a
03

Interpretation layer

Labels with declared origins

Not an adjudication.

Publisher categories are copied from source metadata. Machine signals report observable wording or format and do not determine truth, intent, ethics, or wrongdoing.

  • machine content-type Reported news observable-rules-v1 / 70% rule confidence
  • machine language-signal Death or self-harm observable-rules-v1 / 65% rule confidence
  • publisher category AI (artificial intelligence) rss-category
  • publisher category Breast cancer rss-category
  • publisher category Health rss-category
  • publisher category Heart disease rss-category
  • publisher category High blood pressure rss-category
  • publisher category Society rss-category
  • publisher category Stroke rss-category
  • publisher category Technology rss-category
  • publisher category UK news rss-category
  • publisher category Women's health rss-category
04

Public response layer

Reception snapshots

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Comment counts and samples remain absent until a lawful, source-specific capture method is reviewed. Absence is recorded instead of estimated.

05

Evidence layer

Capture provenance

Capture ID
#3168
Observed
27 Aug 2026, 14:31 UTC
HTTP result
200 / parsed
Raw payload
483,896 bytes, private gzip evidence
Collector
news-ledger/0.1
Public boundary
metadata and excerpt