2024
Extracting Systemic Anticancer Therapy and Response Information From Clinical Notes Following the RECIST Definition
Zuo X, Kumar A, Shen S, Li J, Cong G, Jin E, Chen Q, Warner J, Yang P, Xu H. Extracting Systemic Anticancer Therapy and Response Information From Clinical Notes Following the RECIST Definition. JCO Clinical Cancer Informatics 2024, 8: e2300166. PMID: 38885475, DOI: 10.1200/cci.23.00166.Peer-Reviewed Original ResearchConceptsNatural language processingDomain-specific language modelsNatural language processing systemsInformation extraction systemRule-based moduleNarrative clinical textsNLP tasksEntity recognitionText normalizationAssertion classificationLanguage modelInformation extractionClinical textElectronic health recordsLearning-basedClinical notesLanguage processingTest setSystem performanceHealth recordsResponse extractionTime-consumingAnticancer therapyInformationAssessment information
2022
DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models
Luo C, Islam M, Sheils N, Buresh J, Reps J, Schuemie M, Ryan P, Edmondson M, Duan R, Tong J, Marks-Anglin A, Bian J, Chen Z, Duarte-Salles T, Fernández-Bertolín S, Falconer T, Kim C, Park R, Pfohl S, Shah N, Williams A, Xu H, Zhou Y, Lautenbach E, Doshi J, Werner R, Asch D, Chen Y. DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models. Nature Communications 2022, 13: 1678. PMID: 35354802, PMCID: PMC8967932, DOI: 10.1038/s41467-022-29160-4.Peer-Reviewed Original Research
2021
Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition
Li J, Zhou Y, Jiang X, Natarajan K, Pakhomov S, Liu H, Xu H. Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition. Journal Of The American Medical Informatics Association 2021, 28: 2193-2201. PMID: 34272955, PMCID: PMC8449609, DOI: 10.1093/jamia/ocab112.Peer-Reviewed Original Research