H
He Sui
Researcher at Jilin University
Publications - 14
Citations - 874
He Sui is an academic researcher from Jilin University. The author has contributed to research in topics: Medicine & Feature selection. The author has an hindex of 7, co-authored 11 publications receiving 460 citations.
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Journal ArticleDOI
Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification
Feng Shi,Liming Xia,Fei Shan,Dijia Wu,Ying Wei,Huan Yuan,Huiting Jiang,Yaozong Gao,He Sui,Dinggang Shen +9 more
TL;DR: An infection size-aware random forest method (iSARF) was proposed for discriminating COVID-19 from CAP and yielded its best performance when using the handcrafted features, with a sensitivity and accuracy of 90.7%, a specificity and an accuracy of 89.4% over state-of-the-art classifiers.
Journal ArticleDOI
Diagnosis of Coronavirus Disease 2019 (COVID-19) With Structured Latent Multi-View Representation Learning
Hengyuan Kang,Liming Xia,Fuhua Yan,Zhibin Wan,Feng Shi,Huan Yuan,Huiting Jiang,Dijia Wu,He Sui,Changqing Zhang,Dinggang Shen +10 more
TL;DR: In this article, a unified latent representation is learned which can completely encode information from different aspects of features and is endowed with promising class structure for separability, while the completeness is guaranteed with a group of backward neural networks (each for one type of features), while by using class labels the representation is enforced to be compact within COVID-19/community-acquired pneumonia (CAP).
Journal ArticleDOI
Large-scale screening to distinguish between COVID-19 and community-acquired pneumonia using infection size-aware classification.
Feng Shi,Liming Xia,Fei Shan,Bin Song,Dijia Wu,Ying Wei,Huan Yuan,Huiting Jiang,Yichu He,Yaozong Gao,He Sui,Dinggang Shen +11 more
TL;DR: In this article, a set of handcrafted location-specific features was proposed to best capture the COVID-19 distribution pattern, in comparison to conventional CT severity score (CT-SS) and Radiomics features.
Journal ArticleDOI
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT
Liang Sun,Zhanhao Mo,Fuhua Yan,Liming Xia,Fei Shan,Zhongxiang Ding,Bin Song,Wanchun Gao,Wei Shao,Feng Shi,Huan Yuan,Huiting Jiang,Dijia Wu,Ying Wei,Yaozong Gao,He Sui,Daoqiang Zhang,Dinggang Shen +17 more
TL;DR: Experimental results on the CO VID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.
Journal ArticleDOI
Hypergraph learning for identification of COVID-19 with CT imaging.
Donglin Di,Feng Shi,Fuhua Yan,Liming Xia,Zhanhao Mo,Zhongxiang Ding,Fei Shan,Bin Song,Shengrui Li,Ying Wei,Ying Shao,Miaofei Han,Yaozong Gao,He Sui,Yue Gao,Dinggang Shen,Dinggang Shen +16 more
TL;DR: An Uncertainty Vertex-weighted Hypergraph Learning (UVHL) method to identify COVID-19 from CAP using CT images is proposed, which demonstrates the effectiveness and robustness of the proposed method on the identification of CO VID-19 in comparison to state-of-the-art methods.