Healthcare is one of the most promising areas for machine learning models to make a positive impact.
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning approaches burdens each development task as time and resource intensive.
no code implementations • 11 Aug 2018 • Christopher P. Bridge, Michael Rosenthal, Bradley Wright, Gopal Kotecha, Florian Fintelmann, Fabian Troschel, Nityanand Miskin, Khanant Desai, William Wrobel, Ana Babic, Natalia Khalaf, Lauren Brais, Marisa Welch, Caitlin Zellers, Neil Tenenholtz, Mark Michalski, Brian Wolpin, Katherine Andriole
The amounts of muscle and fat in a person's body, known as body composition, are correlated with cancer risks, cancer survival, and cardiovascular risk.
Medical imaging data sets are often imbalanced as pathologic findings are generally rare, which introduces significant challenges when training deep learning models.