2025
New onset refractory status epilepticus: Long‐term outcomes beyond seizures
Espino P, Eschbach K, Blank L, Cervenka M, Muscal E, Farias‐Moeller R, Gilmore E, Gopaul M, Haider H, Hanin A, Hirsch L, Kellogg M, Kluger G, Lee S, Melendez‐Zaidi A, Navarro V, Oliger A, Pasini E, Reuner G, Sharpe C, Sheikh Z, Steigleder L, Steriade C, Stredny C, Strzelczyk A, Taraschenko O, van Baalen A, Vinette S, Wickström R, Wong N, Yoo J, Gofton T. New onset refractory status epilepticus: Long‐term outcomes beyond seizures. Epilepsia 2025, 66: 988-1005. PMID: 39825688, PMCID: PMC11997932, DOI: 10.1111/epi.18267.Peer-Reviewed Original ResearchQuality of lifeLong-term outcomesCaregiver burdenConsensus-building processDevelopment of targeted management strategiesWorking GroupOutcome domainsLong-term mortalityOutcome measuresConsensus processExpert panelRecovery trajectoriesSurvivorsOutcomesPubMed searchResearch studiesKnowledge gapsCaregiversStandard dataPsychiatric
2024
A general framework for developing computable clinical phenotype algorithms
Carrell D, Floyd J, Gruber S, Hazlehurst B, Heagerty P, Nelson J, Williamson B, Ball R. A general framework for developing computable clinical phenotype algorithms. Journal Of The American Medical Informatics Association 2024, 31: 1785-1796. PMID: 38748991, PMCID: PMC11258420, DOI: 10.1093/jamia/ocae121.Peer-Reviewed Original ResearchNatural language processing methodsStage of algorithm developmentElectronic health record dataLanguage processing methodsHealth record dataGold standard dataMachine learningDevelopment of computational algorithmsPhenotyping algorithmsAlgorithm developmentAlgorithmPractice guidelinesRecord dataAlgorithm development processComputational algorithmDevelopment processProcessing methodsDevelopment projectsStandard dataModel evaluationClinical medicineGuidelinesPractical guidanceInformaticsHealthcare
2020
Efficient and Accurate Extracting of Unstructured EHRs on Cancer Therapy Responses for the Development of RECIST Natural Language Processing Tools: Part I, the Corpus
Li Y, Luo Y, Wampfler J, Rubinstein S, Tiryaki F, Ashok K, Warner J, Xu H, Yang P. Efficient and Accurate Extracting of Unstructured EHRs on Cancer Therapy Responses for the Development of RECIST Natural Language Processing Tools: Part I, the Corpus. JCO Clinical Cancer Informatics 2020, 4: cci.19.00147. PMID: 32364754, PMCID: PMC7265793, DOI: 10.1200/cci.19.00147.Peer-Reviewed Original ResearchConceptsNatural language processing toolsElectronic health recordsLanguage processing toolsGold standard dataUnstructured electronic health recordsProcessing toolsAmount of dataClinical notesStandard dataMayo Clinic electronic health recordsClinic's electronic health recordEnvironment toolsAccurate annotationHealth recordsInformatics toolsEffective analysisData setsTextual sourcesCorpusToolInformationData extractionSetExtractingAnnotation
2018
Impact of linkage quality on inferences drawn from analyses using data with high rates of linkage errors in rural Tanzania
Rentsch CT, Harron K, Urassa M, Todd J, Reniers G, Zaba B. Impact of linkage quality on inferences drawn from analyses using data with high rates of linkage errors in rural Tanzania. BMC Medical Research Methodology 2018, 18: 165. PMID: 30526518, PMCID: PMC6288858, DOI: 10.1186/s12874-018-0632-5.Peer-Reviewed Original Research
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