Xiaoyuan Hou1,2, Hui Zhang1,2, Yan Tan3, Zhenchao Tang1,2, Hui Zhang3, and Jie Tian1,2
1Beijing Advanced Innovation Center for Big Data-Based Precision Medicine(BDBPM) ,Beihang University,100083, Beijing, China, 2Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences,100190, Beijing, China, 3Department of Radiology, First Clinical Medical College, Shanxi Medical University,030001, Taiyuan, China
1Beijing Advanced Innovation Center for Big Data-Based Precision Medicine(BDBPM) ,Beihang University,100083, Beijing, China, 2Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences,100190, Beijing, China, 3Department of Radiology, First Clinical Medical College, Shanxi Medical University,030001, Taiyuan, China
We
found that the proposed multi-task learning model was potent in predicting
multiple genotype of gliomas preoperatively based on MR images. It indicated
that multi-task learning model reached the level of state-of-the-art machine
learning method in predicting genotype.
Figure1. Best-performed multi-task
learning model predicting multiple genotype of gliomas preoperatively based on
MR images.
The figure beside the convolution block means the number of convolution
kernel.
AUC, Area Under Receiver Operating Characteristic Curve
Sharing blocks means the number of blocks different branches owned jointly
Remaining blocks means the number of blocks different branches owned respectively