H
Huiying Zhao
Researcher at Sun Yat-sen University
Publications - 101
Citations - 3199
Huiying Zhao is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 23, co-authored 83 publications receiving 1964 citations. Previous affiliations of Huiying Zhao include Indiana University – Purdue University Indianapolis & Indiana University.
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Journal ArticleDOI
Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images.
Ying Song,Shuangjia Zheng,Liang Li,Xiang Zhang,Xiaodong Zhang,Ziwang Huang,Jianwen Chen,Ruixuan Wang,Huiying Zhao,Yunfei Zha,Jun Shen,Yutian Chong,Yuedong Yang +12 more
TL;DR: Wang et al. as mentioned in this paper developed a deep learning-based CT diagnosis system to identify patients with COVID-19, which achieved an AUC of 0.99, recall (sensitivity) of 0.,93, and precision of 0,96.
Posted ContentDOI
Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images
Song Ying,Shuangjia Zheng,Liang Li,Xiang Zhang,Xiaodong Zhang,Ziwang Huang,Jianwen Chen,Huiying Zhao,Ruixuan Wang,Yutian Chong,Jun Shen,Yunfei Zha,Yuedong Yang +12 more
TL;DR: A deep learning-based CT diagnosis system (DeepPneumonia) was developed and showed that the established models can achieve a rapid and accurate identification of COVID-19 in human samples, thereby allowing identification of patients.
Journal ArticleDOI
Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates
TL;DR: This article reports efforts to further improve a single-method fold recognition technique called SPARKS by changing the alignment scoring function and incorporating the SPINE-X techniques that make improved prediction of secondary structure, backbone torsion angle and solvent accessible surface area.
Journal ArticleDOI
A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts
Christel M. Middeldorp,Anke R. Hammerschlag,Klaasjan G. Ouwens,Maria M. Groen-Blokhuis,Beate St Pourcain,Corina U. Greven,Irene Pappa,Carla M. T. Tiesler,Wei Ang,Ilja M. Nolte,Natalia Vilor-Tejedor,Jonas Bacelis,Jane L. Ebejer,Huiying Zhao,Gareth E. Davies,Erik A. Ehli,David M. Evans,Iryna O. Fedko,Mònica Guxens,Jouke-Jan Hottenga,James J. Hudziak,Astanand Jugessur,John P. Kemp,Eva Krapohl,Nicholas G. Martin,Mario Murcia,Ronny Myhre,Johan Ormel,Susan M. Ring,Marie Standl,Evie Stergiakouli,Camilla Stoltenberg,Elisabeth Thiering,Nicholas J. Timpson,Maciej Trzaskowski,Peter J. van der Most,Carol A. Wang,Dale R. Nyholt,Sarah E. Medland,Benjamin M. Neale,Bo Jacobsson,Jordi Sunyer,Catharina A. Hartman,Andrew J. O. Whitehouse,Craig E. Pennell,Joachim Heinrich,Robert Plomin,George Davey Smith,Henning Tiemeier,Danielle Posthuma,Dorret I. Boomsma +50 more
TL;DR: In this article, the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis.
Journal ArticleDOI
Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets
TL;DR: The superior performance over existing methods indicates the importance of dividing structures into domains, using the Z-score to measure relative structural similarity, and a statistical energy function to measure protein–RNA binding affinity.