Digital Mammography DREAM Challenge

The Digital Mammography DREAM Challenge will attempt to improve the predictive accuracy of digital mammography for the early detection of breast cancer.

Digital Mammography DREAM Challenge

The goal of the Digital Mammography (DM) DREAM Challenge was to apply an open science, crowd-sourced approach to develop and assess algorithms for risk stratification of screening mammograms that can be used to improve breast cancer detection. These algorithms could potentially benefit interpretation of other tumor imaging, impacting a wide set of cancer patients. The DM Challenge encouraged teams to apply deep learning methods to a large set of mammography images of over 640k images from 80k women. Dozens of teams participated in this Challenge, resulting in the development of many novel approaches to cancer detection and the establishment of public standards and benchmarks in this field.

Read our our press release announcing the winners of the first phase of the DM Challenge.


Other Assessments & Benchmarking research studies

ICGC-TCGA DREAM Somatic Mutation Calling – RNA Challenge

The ICGC-TCGA DREAM Somatic Mutation Calling - RNA Challenge is an international effort to improve standard methods for identifying cancer-associated rearrangements in RNA sequencing (RNA-seq) data.

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Multiple Myeloma DREAM Challenge

The Multiple Myeloma DREAM Challenge aims to accelerate the development and evaluation of models for risk stratification of patients to improve therapeutic decision-making.

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Digital Mammography DREAM Challenge

The Digital Mammography DREAM Challenge will attempt to improve the predictive accuracy of digital mammography for the early detection of breast cancer.

Learn More