no code implementations • 18 Mar 2023 • David A. Clunie, Adam Flanders, Adam Taylor, Brad Erickson, Brian Bialecki, David Brundage, David Gutman, Fred Prior, J Anthony Seibert, John Perry, Judy Wawira Gichoya, Justin Kirby, Katherine Andriole, Luke Geneslaw, Steve Moore, TJ Fitzgerald, Wyatt Tellis, Ying Xiao, Keyvan Farahani
Only technical issues of public sharing are addressed.
no code implementations • 2 Mar 2020 • Charles Lu, Julia Strout, Romane Gauriau, Brad Wright, Fabiola Bezerra De Carvalho Marcruz, Varun Buch, Katherine Andriole
Healthcare is one of the most promising areas for machine learning models to make a positive impact.
no code implementations • 29 Oct 2019 • Neil Deshmukh, Selin Gumustop, Romane Gauriau, Varun Buch, Bradley Wright, Christopher Bridge, Ram Naidu, Katherine Andriole, Bernardo Bizzo
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.
no code implementations • 26 Jul 2018 • Hoo-chang Shin, Neil A. Tenenholtz, Jameson K Rogers, Christopher G Schwarz, Matthew L Senjem, Jeffrey L Gunter, Katherine Andriole, Mark Michalski
Medical imaging data sets are often imbalanced as pathologic findings are generally rare, which introduces significant challenges when training deep learning models.