Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture
Michael A. Silva(University of Miami), Nirav J. Patel(Brigham and Women's Hospital), James M. Brown(Mary Lyon Centre at MRC Harwell), Alfred P. See(Boston Children's Hospital), Jayashree Kalpathy–Cramer(University of Colorado Denver), Ken Chang(Harvard University), Omar Arnaout(Brigham and Women's Hospital), William B. Gormley(Brigham and Women's Hospital), Katharina Hoebel(Harvard University), Jay Patel(Boston University), Vasileios K. Kavouridis(Brigham and Women's Hospital), Andrew Beers(Massachusetts General Hospital), Troy Gallerani(Brigham and Women's Hospital), Mohammad Ali Aziz‐Sultan(Brigham and Women's Hospital)
Cited by 69
Related Papers
3D Slicer as an image computing platform for the Quantitative Imaging Network
|Magnetic Resonance Imaging|2012|9.1k
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
|IEEE Transactions on Medical Imaging|2014|6.7k
High-throughput discovery of novel developmental phenotypes
|Nature|2016|1.3k
Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials
|Neuro-Oncology|2015|670
Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks
|JAMA Ophthalmology|2018|660