most citedDeep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review

250 citations · 252 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG20202 cited

Cyclic Label Propagation for Graph Semi-supervised Learning

Zhao Li, Yixin Liu, Zhen Zhang +3

Graph neural networks (GNNs) have emerged as effective approaches for graph analysis, especially in the scenario of semi-supervised learning. Despite its success, GNN often suffers…

cs.LG2020250 cited

Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review

Yuqi Si, Jingcheng Du, Zhao Li +5

Patient representation learning refers to learning a dense mathematical representation of a patient that encodes meaningful information from Electronic Health Records (EHRs). This…

cs.SI2020

A Survey on Contact Tracing: the Latest Advancements and Challenges

Ting Jiang, Yang Zhang, Minhao Zhang +7

Infectious diseases are caused by pathogenic microorganisms, such as bacteria, viruses, parasites or fungi, which can be spread, directly or indirectly, from one person to another.…

cs.AI2020

Method and Dataset Entity Mining in Scientific Literature: A CNN + Bi-LSTM Model with Self-attention

Linlin Hou, Ji Zhang, Ou Wu +6

Literature analysis facilitates researchers to acquire a good understanding of the development of science and technology. The traditional literature analysis focuses largely on the…

cs.CL2018

Automatic Generation of Chinese Short Product Titles for Mobile Display

Yu Gong, Xusheng Luo, Kenny Q. Zhu +3

This paper studies the problem of automatically extracting a short title from a manually written longer description of E-commerce products for display on mobile devices. It is a ne…

cs.CL2018

Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant

Yu Gong, Xusheng Luo, Yu Zhu +6

Slot filling is a critical task in natural language understanding (NLU) for dialog systems. State-of-the-art approaches treat it as a sequence labeling problem and adopt such model…