2015
A comparative study of disease genes and drug targets in the human protein interactome
Sun J, Zhu K, Zheng W, Xu H. A comparative study of disease genes and drug targets in the human protein interactome. BMC Bioinformatics 2015, 16: s1. PMID: 25861037, PMCID: PMC4402590, DOI: 10.1186/1471-2105-16-s5-s1.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesDisease genesDrug targetsHuman protein-coding genesHuman protein-protein interaction networkProtein-protein interaction networkProtein-coding genesHuman protein interactomeComplex diseasesNovel drug targetsProtein interactomeAnatomical Therapeutic Chemical (ATC) classificationInteraction networksDisease proteinAssociation studiesGenesDisease categoriesInteractomeProteinMajor disease categoriesDifferent disease categoriesFirst comprehensive comparisonTargetTreatment efficacyHigh betweenness
2014
Network‐Assisted Prediction of Potential Drugs for Addiction
Sun J, Huang L, Xu H, Zhao Z. Network‐Assisted Prediction of Potential Drugs for Addiction. BioMed Research International 2014, 2014: 258784. PMID: 24689033, PMCID: PMC3932722, DOI: 10.1155/2014/258784.Peer-Reviewed Original Research
2013
Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features
Tang B, Cao H, Wu Y, Jiang M, Xu H. Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features. BMC Medical Informatics And Decision Making 2013, 13: s1. PMID: 23566040, PMCID: PMC3618243, DOI: 10.1186/1472-6947-13-s1-s1.Peer-Reviewed Original ResearchConceptsStructural support vector machineWord representation featuresClinical NER tasksConditional Random FieldsSupport vector machinePerformance of MLClinical NER systemMachine learningRepresentation featuresNER systemNER taskVector machineEntity recognitionNatural language processing researchSequential labeling algorithmClinical entity recognitionLarge margin theoryClinical text processingLanguage processing researchPerformance of CRFsHighest F-measureClinical NLP researchI2b2 NLP challengeSame feature setsBetter performance
2012
A new clustering method for detecting rare senses of abbreviations in clinical notes
Xu H, Wu Y, Elhadad N, Stetson P, Friedman C. A new clustering method for detecting rare senses of abbreviations in clinical notes. Journal Of Biomedical Informatics 2012, 45: 1075-1083. PMID: 22742938, PMCID: PMC3729222, DOI: 10.1016/j.jbi.2012.06.003.Peer-Reviewed Original Research
2008
Methods for Building Sense Inventories of Abbreviations in Clinical Notes
Xu H, Stetson P, Friedman C. Methods for Building Sense Inventories of Abbreviations in Clinical Notes. Journal Of The American Medical Informatics Association 2008, 16: 103-108. PMID: 18952935, PMCID: PMC2605589, DOI: 10.1197/jamia.m2927.Peer-Reviewed Original Research