Using regular expressions to abstract blood pressure and treatment intensification information from the text of physician notes.
about
Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resourceAn online spaced-education game among clinicians improves their patients' time to blood pressure control: a randomized controlled trial.Performance of a Natural Language Processing (NLP) Tool to Extract Pulmonary Function Test (PFT) Reports from Structured and Semistructured Veteran Affairs (VA) DataComparison of information content of structured and narrative text data sources on the example of medication intensificationDocumentation of body mass index and control of associated risk factors in a large primary care network.Prevalence and factors affecting home blood pressure documentation in routine clinical care: a retrospective study.Identification of misspelled words without a comprehensive dictionary using prevalence analysis.Enriching the international clinical nomenclature with Chinese daily used synonyms and concept recognition in physician notes.Data from clinical notes: a perspective on the tension between structure and flexible documentation.Linking electronic health record-extracted psychosocial data in real-time to risk of readmission for heart failureConstructing a population-based research database from routine maternal screening records: a resource for studying alloimmunization in pregnant women.Unbiased identification of patients with disorders of sex development.Chapter 13: Mining electronic health records in the genomics era.Using information from the electronic health record to improve measurement of unemployment in service members and veterans with mTBI and post-deployment stress.Systolic blood pressure and short-term mortality in the emergency department and prehospital setting: a hospital-based cohort study.Natural language processing in pathology: a scoping review.Towards automatic diabetes case detection and ABCS protocol compliance assessment.Desiderata for computable representations of electronic health records-driven phenotype algorithms.A study of actions in operative notesLexical concept distribution reflects clinical practice.Facilitating Clinical Outcomes Assessment through the automated identification of quality measures for prostate cancer surgery.The Clinical Outcomes Assessment Toolkit: a framework to support automated clinical records-based outcomes assessment and performance measurement research.Encounter frequency and serum glucose level, blood pressure, and cholesterol level control in patients with diabetes mellitusNew Paradigms for Patient-Centered Outcomes Research in Electronic Medical Records: An Example of Detecting Urinary Incontinence Following Prostatectomy.Meaningful measurement: developing a measurement system to improve blood pressure control in patients with chronic kidney disease.Shock in the emergency department; a 12 year population based cohort studyEncounter frequency and blood pressure in hypertensive patients with diabetes mellitusAutomatic identification and classification of surgical margin status from pathology reports following prostate cancer surgeryUsing regular expressions to extract information on pacemaker implantation procedures from clinical reports.Automated extraction of clinical traits of multiple sclerosis in electronic medical records.The challenge of measuring quality of care from the electronic health record.Automated outcome classification of emergency department computed tomography imaging reports.A systematic literature review of automated clinical coding and classification systemsIdentification of documented medication non-adherence in physician notes.A De-identification method for bilingual clinical texts of various note types.TagLine: Information Extraction for Semi-Structured Text in Medical Progress Notes.Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners.Extracting Healthcare Quality Information from Unstructured Data.Rewriting Natural Language Queries Using Patterns
P2860
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P2860
Using regular expressions to abstract blood pressure and treatment intensification information from the text of physician notes.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh
2006年學術文章
@zh-hant
name
Using regular expressions to a ...... m the text of physician notes.
@en
Using regular expressions to a ...... m the text of physician notes.
@nl
type
label
Using regular expressions to a ...... m the text of physician notes.
@en
Using regular expressions to a ...... m the text of physician notes.
@nl
prefLabel
Using regular expressions to a ...... m the text of physician notes.
@en
Using regular expressions to a ...... m the text of physician notes.
@nl
P2093
P2860
P356
P1476
Using regular expressions to a ...... om the text of physician notes
@en
P2093
Alexander Turchin
Eric C Makhni
Jonathan S Einbinder
Merri L Pendergrass
Nikheel S Kolatkar
P2860
P304
P356
10.1197/JAMIA.M2078
P577
2006-08-23T00:00:00Z