activity
20192021
most citedLearning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

30 citations · 44 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL20211 cited

Graphine: A Dataset for Graph-aware Terminology Definition Generation

Zequn Liu, Shukai Wang, Yiyang Gu +3

Precisely defining the terminology is the first step in scientific communication. Developing neural text generation models for definition generation can circumvent the labor-intens…

eess.IV202030 cited

Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction

Jiafa He, Chengwei Pan, Can Yang +4

Automatic blood vessel extraction from 3D medical images is crucial for vascular disease diagnoses. Existing methods based on convolutional neural networks (CNNs) may suffer from d…

eess.IV2020

Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation

Yicheng Wu, Chengwei Pan, Shuqi Wang +3

Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases. Although being ext…

cs.LG202010 cited

Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases

Luchen Liu, Zequn Liu, Haoxian Wu +4

Mortality prediction of diverse rare diseases using electronic health record (EHR) data is a crucial task for intelligent healthcare. However, data insufficiency and the clinical d…

cs.LG2019

Predictive Multi-level Patient Representations from Electronic Health Records

Zichang Wang, Haoran Li, Luchen Liu +2

The advent of the Internet era has led to an explosive growth in the Electronic Health Records (EHR) in the past decades. The EHR data can be regarded as a collection of clinical e…

cs.LG20193 cited

Early Prediction of Sepsis From Clinical Datavia Heterogeneous Event Aggregation

Luchen Liu, Haoxian Wu, Zichang Wang +2

Sepsis is a life-threatening condition that seriously endangers millions of people over the world. Hopefully, with the widespread availability of electronic health records (EHR), p…