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Fast AUC Maximization Learning Machine With Simultaneous Outlier Detection Journal article
Sun, Yichen, Vong, Chi Man, Wang, Shitong. Fast AUC Maximization Learning Machine With Simultaneous Outlier Detection[J]. IEEE Transactions on Cybernetics, 2022, 53(11), 6843 - 6857.
Authors:  Sun, Yichen;  Vong, Chi Man;  Wang, Shitong
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:9.4/10.3 | Submit date：2022/05/17
Anomaly Detection  Auc Maximization  Imbalance Classification  Kernel  Minimum Enclosing Ball (Meb)  Outlier Detection  Support Vector Machines  Task Analysis  Time Complexity  Training  Upper Bound  
Identification of deleterious variants of uncertain significance in BRCA2 BRC4 repeat through molecular dynamics simulations Journal article
Sinha, Siddharth, Qin, Zixin, Tam, Benjamin, Wang, San Ming. Identification of deleterious variants of uncertain significance in BRCA2 BRC4 repeat through molecular dynamics simulations[J]. Briefings in functional genomics, 2022, 21(3), 202-215.
Authors:  Sinha, Siddharth;  Qin, Zixin;  Tam, Benjamin;  Wang, San Ming
Favorite | TC[WOS]:4 TC[Scopus]:4  IF:2.5/3.4 | Submit date：2022/06/10
Brca2 Brc4  Auc  Deleterious  Molecular Dynamics Simulations  Pca  Roc  Tolerated  Vus Classification  
Abnormal dynamic functional connectivity and brain states in Alzheimer’s diseases: functional near-infrared spectroscopy study Journal article
Haijing Niu, Zhaojun Zhu, Mengjing Wan, Xuanyu Li, Zhen Yuan, Yu Sun, Ying Han. Abnormal dynamic functional connectivity and brain states in Alzheimer’s diseases: functional near-infrared spectroscopy study[J]. Neurophotonics, 2019, 6(2), 025010.
Authors:  Haijing Niu;  Zhaojun Zhu;  Mengjing Wan;  Xuanyu Li;  Zhen Yuan; et al.
Adobe PDF | Favorite | TC[WOS]:32 TC[Scopus]:32 | Submit date：2022/08/21
CommunicAtion WithIn The BraIn Is Highly Dynamic. AlzheI.e.’s dIseAse (Ad) ExhibIts Dynamic.progression COrrespondIng To a DeclIne In MemOry And Cognition. HoWever, Little Is Known Of wheTher BraIn Dynamic. Are dIsrupted In Ad And Its Prodromal Stage, Mild CognitI.e.impairment (Mci). FOr Our Study, We AcquI.e. High samplIng RAte Functional near-InfrAred Spectroscopy imagIng DAta At Rest From The EntI.e.cOrtex Of 23 pAtients With Ad Dementia, 25 pAtients With Amnestic Mild CognitI.e.impairment (aMci), And 30 age-mAtched Healthy Controls (Hcs). slidIng-wIndow cOrrelAtion And K-means clusterIng Analyses Were Used To Construct Dynamic.Functional Connectivity (Fc) Maps FOr Each Participant. We dIscovered thAt The BraIn’s Dynamic.Fc Variability Strength (q) Significantly IncreAsed In Both aMci And Ad Group As compAred To Hcs. usIng The q Value As a meAsurement, The clAssificAtion perFOrmance ExhibI.e. a Good poWer In differentiAtIng aMci [Area Under The Curve (Auc ¼ 82.5%)] Or Ad (Auc ¼ 86.4%) From Hcs. furThermOre, We Identified Two abnOrmal BraIn Fc stAtes In The Ad Group, Of Which The Occurrence Frequency (f) ExhibI.e. a Significant decreAse FOr The First-level Fc stAte (stAte 1) And a Significant IncreAse FOr The Second-level Fc stAte (stAte 2). We Also Found thAt The abnOrmal f In These Two stAtes Significantly cOrrelAted With The CognitI.e.impairment In pAtients. These fIndIngs provI.e.The First EvI.e.ce To demonstRAte The dIsruptions Of Dynamic.BraIn Connectivity In aMci And Ad And Extend The trAditional stAtic (I.e., tI.e.averaged) Fc fIndIngs In The dIseAse (I.e., dIsconnection Syndrome) And Thus provI.e.Insights InTo UnderstAndIng The pAthophysiological mechanIsms occurrIng In aMci And Ad.  
Credit Scoring Models with AUC Maximization Based on Weighted SVM Journal article
LIGANG ZHOU, KIN KEUNG LAI, JEROME YEN. Credit Scoring Models with AUC Maximization Based on Weighted SVM[J]. International Journal of Information Technology and Decision Making, 2009, 8(4), 677- 696.
Authors:  LIGANG ZHOU;  KIN KEUNG LAI;  JEROME YEN
Favorite | TC[WOS]:41 TC[Scopus]:45  IF:2.5/2.4 | Submit date：2019/12/11
Credit Scoring  Features Weighting  Svm  Auc