Data coverage
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. RSNA collected screening mammograms and supporting information from two sites, totaling just under 20,000 imaging studies.
Access & permitted use
Review the publisher’s documentation for availability, eligibility and permitted uses, including commercial analysis, model training and redistribution.
You may access and use these de-identified imaging datasets and annotations (“the data”) for non-commercial purposes only, including academic research and education, as long as you agree to abide by the following provisions: Not to make any attempt to identify or contact any individual(s) who may be the subjects of the data. You may not share or redistribute a copy of any portion or all of the data in any form. If you reference the data in published material, include a citation to the “Radiological Society of North America Screening Mammography Breast Cancer Detection (RSNA-SMBC) Dataset, November 2022” [https://doi.org/10.1148/dataset.smbc.2024].
Need help sourcing data?
Tell us your required fields, population, geography and time period. We can review suitable sources and licensing options.
Request sourcing help