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100+ datasets found
  1. Mammography Breast Cancer Detection

    Updated Dec 28, 2022
  2. p

    Data from: VinDr-Mammo: A large-scale benchmark dataset for computer-aided...

    Updated Mar 21, 2022
  3. g

    Mammograms from cancer screening

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  4. n

    Breast Cancer Screening (Survey)

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  5. RSNA Breast Cancer Detection - PNG/256/nearest

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  6. S

    CSAW-CC (mammografi) – ett dataset för AI-forskning för att förbättra...

    csv, docx
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  7. Share of women screened for breast cancer in Italy 2020-2021, by region

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  8. Breast Cancer Detection Dataset

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  9. f

    DataSheet_1_Association of Breast Cancer Screening Behaviors With Stage at...

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  10. s

    BELA: evaluation of population preferences to breast cancer screening in...

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  11. f

    sj-xlsx-2-bcb-10.1177_11782234211043651 – Supplemental material for...

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  12. a

    Health Indicator - Breast Cancer Screening

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    Updated May 15, 2015
  13. d

    Data from: Breast Screening Programme

    Updated Jan 28, 2021
  14. d

    Data from: Breast Screening Programme

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  15. A

    ‘Breast cancer prediction’ analyzed by Analyst-2

    Updated Feb 14, 2022
  16. Share of U.S. women screened for breast cancer in the past two years, 2018,...

    Updated May 28, 2021
  17. d

    Data from: Breast Screening Programme

    Updated Feb 28, 2019
  18. d

    Cancer screening coverage - breast cancer (% eligible women screened...

    • +1more
    Updated Aug 11, 2022
  19. r

    Data from: Assessing the impact of counterfactual thinking messages for...

    Updated Oct 30, 2019
  20. s

    Data from: CSAW-M: An Ordinal Classification Dataset for Benchmarking...

    Updated Dec 3, 2021
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Gaurav Dutta (2022). Mammography Breast Cancer Detection [Dataset].
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Mammography Breast Cancer Detection

Mammography Breast Cancer Detection

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74 scholarly articles cite this dataset (View in Google Scholar)
zip(1049224527 bytes)Available download formats
Dataset updated
Dec 28, 2022
Gaurav Dutta

Attribution 4.0 (CC BY 4.0)
License information was derived automatically


Goal of the Competition The goal of this competition is to identify breast cancer. You'll train your model with screening mammograms obtained from regular screening.

Your work improving the automation of detection in screening mammography may enable radiologists to be more accurate and efficient, improving the quality and safety of patient care. It could also help reduce costs and unnecessary medical procedures.

Context According to the WHO, breast cancer is the most commonly occurring cancer worldwide. In 2020 alone, there were 2.3 million new breast cancer diagnoses and 685,000 deaths. Yet breast cancer mortality in high-income countries has dropped by 40% since the 1980s when health authorities implemented regular mammography screening in age groups considered at risk. Early detection and treatment are critical to reducing cancer fatalities, and your machine learning skills could help streamline the process radiologists use to evaluate screening mammograms.

Currently, early detection of breast cancer requires the expertise of highly-trained human observers, making screening mammography programs expensive to conduct. A looming shortage of radiologists in several countries will likely worsen this problem. Mammography screening also leads to a high incidence of false positive results. This can result in unnecessary anxiety, inconvenient follow-up care, extra imaging tests, and sometimes a need for tissue sampling (often a needle biopsy).

The competition host, the Radiological Society of North America (RSNA) is a non-profit organization that represents 31 radiologic subspecialties from 145 countries around the world. RSNA promotes excellence in patient care and health care delivery through education, research, and technological innovation.

Your efforts in this competition could help extend the benefits of early detection to a broader population. Greater access could further reduce breast cancer mortality worldwide.

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