The Digital Mammography DREAM Challenge

数字乳房x线摄影梦想挑战将尝试提高数字乳房x线摄影的预测准确性，以早期发现乳腺癌。这项挑战的主要好处是建立新的定量工具-机器学习，深度学习或其他-可以帮助降低筛查乳房x线照相术的召回率，并可能影响将常规乳腺癌筛查的平衡转向更多的收益和更少的伤害。参与团队将被要求提交基于来自86000多个受试者的640,000多个去识别的数字乳房x线摄影图像的预测模型，以及相应的临床变量。

The Digital Mammography Dream Challenge aims to improve the predictive accuracy of digital mammography for the early detection of breast cancer. The core benefit of this challenge is to develop novel quantitative tools—including machine learning, deep learning, or other approaches—that can help reduce the recall rate in screening mammography and potentially shift the balance of routine breast cancer screening toward greater benefit and less harm. Participating teams will be required to submit predictive models built on over 640,000 de-identified digital mammography images from more than 86,000 subjects, along with corresponding clinical variables.

搜集汇总

背景与挑战

背景概述

该数据集是数字乳房X线摄影DREAM挑战的数据集，旨在通过机器学习或深度学习模型提高乳腺癌早期检测的预测准确性，目标是降低筛查召回率并优化筛查效益。数据集包含来自86,000多名受试者的640,000多张去识别化图像及临床变量，由IBM Research和Sage Bionetworks于2016年发布。