24 citations · 27 across the 3 of their papers we have counts for
7 papers
CATNet: Cross-event Attention-based Time-aware Network for Medical Event Prediction
Sicen Liu, Xiaolong Wang, Yang Xiang +3
Medical event prediction (MEP) is a fundamental task in the medical domain, which needs to predict medical events, including medications, diagnosis codes, laboratory tests, procedu…
3D Brain Reconstruction by Hierarchical Shape-Perception Network from a Single Incomplete Image
Bowen Hu, Baiying Lei, Shuqiang Wang +4
3D shape reconstruction is essential in the navigation of minimally-invasive and auto robot-guided surgeries whose operating environments are indirect and narrow, and there have be…
Decomposing Word Embedding with the Capsule Network
Xin Liu, Qingcai Chen, Yan Liu +4
Word sense disambiguation tries to learn the appropriate sense of an ambiguous word in a given context. The existing pre-trained language methods and the methods based on multi-emb…
Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Xianpei Han, Zhichun Wang, Jiangtao Zhang +22
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks. CCKS 2019 held an evaluation…
Semi-supervised Visual Feature Integration for Pre-trained Language Models
Lisai Zhang, Qingcai Chen, Dongfang Li +1
Integrating visual features has been proved useful for natural language understanding tasks. Nevertheless, in most existing multimodal language models, the alignment of visual and…
A Method to Learn Embedding of a Probabilistic Medical Knowledge Graph: Algorithm Development
Linfeng Li, Peng Wang, Yao Wang +5
This paper proposes an algorithm named as PrTransH to learn embedding vectors from real world EMR data based medical knowledge. The unique challenge in embedding medical knowledge…