RSNA Screening Mammography Breast Cancer Detection AI Challenge (2023)

The 2023 RSNA Screening Mammography Breast Cancer Detection AI Challenge invited participants to develop AI models that can aid in the detection of breast cancer and was conducted on a platform provided by Kaggle, Inc.

Submissions for the competition are closed. Following validation of the results, winners will be announced in late April.

About the 2023 AI Challenge

Breast cancer is the most commonly occurring cancer worldwide, according to the World Health Organization. In 2020 alone, there were 2.3 million new breast cancer diagnoses and 685,000 deaths. Early detection and treatment are critical to reducing cancer fatalities.

“This diverse, well-curated dataset may be used to assess the generalizability to diverse patient populations. The RSNA Screening Mammography Breast Cancer Detection AI Challenge will catalyze collaboration to improve the diagnostic accuracy of screening mammography and save patients’ lives,” said Linda Moy, MD, a professor of radiology at the NYU Grossman School of Medicine and editor designate of the journal Radiology.

Machine learning and AI tools can also help streamline the process radiologists use to evaluate screening mammograms. “Large, curated datasets that the RSNA assembles for AI Challenges are a key resource driving improvement in radiology AI,” said John Mongan, MD, PhD, a professor of radiology at the University of California, San Francisco and chair of the RSNA Machine Learning Steering Committee. “We anticipate that we will see an acceleration in mammography AI activity after release of this dataset, as we have seen in other areas with release of previous datasets.”

About the imaging data

The dataset was contributed by mammography screening programs in Australia and the U.S. It includes detailed labels, with radiologists’ evaluations and follow-up pathology results for suspected malignancies.

The accuracy of machine learning models developed by contestants to detect cancer will be evaluated against this ground truth dataset. At the conclusion of the challenge, the dataset will remain available for use in further research.

This challenge is part of a broader research project that will examine how models generated in the competition perform against previously unseen data and compare their performance to that of expert human observers. These questions are critical in determining how AI tools will perform in clinical settings.

Recognition for winning teams

The winning teams will be recognized at an event during RSNA 2023 (Nov. 26–30, 2023). A $50,000 prize will be award and split between the top teams.

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