… of diagnosis and treatment plans. We summarize the latest advances of radiomic and deep
learning … recurrence after thermal ablation of colorectal cancer liver metastasis[J]. European …

… Deep learning methods are also being used to predetermine complex drug-drug interactions
that may be beneficial or harmful when used as drug “cocktails” in human patients (Kpanou …

… the network resulting in a total accuracy of 77% with a FDR of 0.63 per hour. A comprehensive
primer to the convolutional neural network … detection using deep convolutional neural net…

… is not associated with increased likelihood of nodal metastases [J]. Ann Surg Oncolꎬ 2014ꎬ
… Computer-aided lung cancer diagnosis approaches based on deep learning [ J]. Journal of …

… Method This paper proposes a convolutional neural network … structure and global context
information from high- and low-magnification images,respectively,through a spatial attention …

… The first report of an infected patient in Thailand, a generalized spread in China and worldwide
… Orders of Structure Structures might be spatially open or closed. Open structures display …

… of deep learning technology, some deep learning models have … node metastasis status
prediction of early-stage breast cancer … SAFNet: A deep spatial attention network with classifier …

… QIAO Dapeng 365 Localization of the Offshore Pollutant in Lakes Using Spatial-temporal
Filtering ............................................................ LI Wei, CHAI Li, LUO Xu, YANG Jun 371 An Energy-…

… We briefly introduce popular deep models, including convolutional neural networks, fully …
Spatial clockwork recurrent neural network for muscle perimysium segmentation. In: …

… :A deep convolutional neural network framework to evaluate the risk of lung cancer recurrence
and metastasis from … Recalibrating fully convolutional networks with spatial and channel “…