2018
Analysis of treatment pathways for three chronic diseases using OMOP CDM
Zhang X, Wang L, Miao S, Xu H, Yin Y, Zhu Y, Dai Z, Shan T, Jing S, Wang J, Zhang X, Huang Z, Wang Z, Guo J, Liu Y. Analysis of treatment pathways for three chronic diseases using OMOP CDM. Journal Of Medical Systems 2018, 42: 260. PMID: 30421323, PMCID: PMC6244882, DOI: 10.1007/s10916-018-1076-5.Peer-Reviewed Original ResearchMeSH KeywordsChinaChronic DiseaseCritical PathwaysDatabases, FactualElectronic Health RecordsHumansModels, TheoreticalObservationConceptsTreatment pathwaysChronic diseasesStudy of drugsClinical data repositoryClinical treatmentDifferent medical institutionsProportion of monotherapyFirst-line medicationMedical institutionsFirst Affiliated HospitalType 2 diabetesNanjing Medical UniversityDifferent treatment pathwaysMost patientsCommon medicationsAffiliated HospitalMedicationsNational guidelinesMedication informationLocal hospitalMedical UniversitySame diseaseDiseasePatientsNew drugs
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