Photo Credit: Steve Mabon, Tom Misteli, NCI Center for Cancer Research, National Cancer Institute, National Institutes of Health More than 2,000 teams compete in 2018 Data Science Bowl. When it comes to developing [...]
In our last blog post we described an end-to-end deep learning solution to this challenge. By “end-to-end” we mean that the raw pixels constituting a SAX study for an individual patient were fed into a [...]
This year is the first time that Booz Allen and NVIDIA have partnered to enter a team into the Data Science Bowl. Our goal for this combined team was to share some of our successes [...]
We just made a contest submission scoring 0.022886, placing us 14th on the leaderboard as of February 2nd. In this post we'll outline our current approach and some of the challenges we think we'll face [...]
The dataset for the 2016 Data Science Bowl presents several challenges for automated exploitation. As the images were collected in a real world setting, with several types of sensors, there is a great deal of [...]
