CONVOLUTIONAL NEURAL NETWORKS FOR PREDICTING MOLECULAR PROFILES OF NON-SMALL CELL LUNG CANCER

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室

	CONVOLUTIONAL NEURAL NETWORKS FOR PREDICTING MOLECULAR PROFILES OF NON-SMALL CELL LUNG CANCER
	Dongdong,Yu; Mu,Zhou; Feng,Yang; Di,Dong; Olivier,Gevaert; Zaiyi,Liu; Jingyun,Shi; Jie,Tian
	2017
会议日期	2017.04.17-2017.04.22
会议地点	澳大利亚墨尔本
关键词	Non-small Cell Lung Carcinoma Convolutional Neural Networks Computed Tomography Computed-aided Diagnosis
英文摘要	Quantitative imaging biomarkers identification has become a powerful tool for predictive diagnosis given increasingly available clinical imaging data. In parallel, molecular profiles have been well documented in non-small cell lung cancers (NSCLCs). However, there has been limited studies on leveraging the two major sources for improving lung cancer computer-aided diagnosis. In this paper, we investigate the problem of predicting molecular profiles with CT imaging arrays in NSCLC. In particular, we formulate a discriminative convolutional neural network to learn deep features for predicting epidermal growth factor receptor (EGFR) mutation states that are associated with cancer cell growth. We evaluated our approach on two independent datasets including a discovery set with 595 patients (Datset1) and a validation set with 89 patients (Dataset2). Extensive experimental results demonstrated that the learned CNN-based features are effective in predicting EGFR mutation states (AUC=0.828, ACC=76.16%) on Dataset1, and it further demonstrated generalized predictive performance (AUC=0.668, ACC=67.55%) on Dataset2.
会议录	IEEE International Symposium on Biomedical Imaging. 2017.
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/41044]
专题	自动化研究所_复杂系统管理与控制国家重点实验室
通讯作者	Jie,Tian
推荐引用方式 GB/T 7714	Dongdong,Yu,Mu,Zhou,Feng,Yang,et al. CONVOLUTIONAL NEURAL NETWORKS FOR PREDICTING MOLECULAR PROFILES OF NON-SMALL CELL LUNG CANCER[C]. 见:. 澳大利亚墨尔本. 2017.04.17-2017.04.22.