October 2, 2014
  • Building communities to advance science

DREAM Challenges pose fundamental questions about systems biology and translational medicine. Designed and run by a community of researchers from a variety of organizations, our challenges invite participants to propose solutions — fostering collaboration and building communities in the process. Expertise and institutional support are provided by Sage Bionetworks, along with the infrastructure to host challenges via their Synapse platform. Together, we share a vision allowing individuals and groups to collaborate openly so that the  “wisdom of the crowd” provides the greatest impact on science and human health.
Sage

FEATURED PUBLICATION

Keller A, Gerkin R, et. al.  Predicting human olfactory perception from chemical features of odor molecules; Science; 24 Feb 2017; Vol 355; Issue 6327;  820-826; DOI: 10.1126/science.aai2014  

FEATURED CONTENT

The DREAM Challenge team discuss what DREAM Means to them in this new DREAM Challenges Video produced at the 2016 conference in Phoenix.  

CHALLENGE RESULTS

DREAM 10 – ALS Stratification Prize4Life Challenge

Final results available. »more

DREAM 9.5 Prostate Cancer DREAM Challenge

Final results available. »more

DREAM 9.5 -DREAM Olfaction Prediction Challenge

Final results available. »more  
June 2, 2017

IBM and Sage Bionetworks announce winners of first phase of DREAM Digital Mammography Challenge

IBM and Sage Bionetworks announced today the winners of the first phase of its DREAM Digital Mammography (DM) Challenge have developed algorithms that had 5% fewer false-positive errors in breast cancer screenings than recently published state of the art computerized methods1. This 5 percent improvement could potentially lead to less anxiety and unnecessary procedures for an estimated two million women per year in the United States and could help reduce costs associated with follow-up exams and biopsies. (Read more)

June 2, 2017

Can Machine Learning Help Improve Accuracy in Breast Cancer Screening?

Breast Cancer is the most common cancer in women. It is estimated that one out of eight women will be diagnosed with breast cancer in their lifetime. The good news is that 99 percent of women whose breast cancer was detected early (stage 1 or 0) survive beyond five years after diagnosis, leading countries around the world to implement breast cancer screening programs for early detection. (Read more)

May 5, 2017

Will Machine Learning….

New commentary from the organizers of the DREAM Digital Mammography Challenge in JAMA Oncology asks “Will Machine Learning Tip the Balance in Breast Cancer Screening?” The article discusses the ongoing challenge and how this DREAM Challenge is working to answer that question. (Read more)