Chapter 13: Mining electronic health records in the genomics era.
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Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortalityBiobanks and personalized medicinePhenome-wide association studies on a quantitative trait: application to TPMT enzyme activity and thiopurine therapy in pharmacogenomicsThe role of ontologies in biological and biomedical research: a functional perspectiveA Modular Architecture for Electronic Health Record-Driven PhenotypingExtracting research-quality phenotypes from electronic health records to support precision medicineValidation and enhancement of a computable medication indication resource (MEDI) using a large practice-based datasetReview and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research.Caveats for the use of operational electronic health record data in comparative effectiveness research.Applying active learning to high-throughput phenotyping algorithms for electronic health records dataCombining structured and unstructured data to identify a cohort of ICU patients who received dialysis.Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record.Quantifying a rare disease in administrative data: the example of calciphylaxisRecommendations for the use of operational electronic health record data in comparative effectiveness research.Learning statistical models of phenotypes using noisy labeled training data.A General Framework for Considering Selection Bias in EHR-Based Studies: What Data Are Observed and Why?Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data.Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st CenturyPhenome-Wide Association Studies as a Tool to Advance Precision Medicine.Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.Effectively processing medical term queries on the UMLS Metathesaurus by layered dynamic programming.Deciphering next-generation pharmacogenomics: an information technology perspective.The electronic health record for translational research.Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.Design patterns for the development of electronic health record-driven phenotype extraction algorithms.Evaluation of matched control algorithms in EHR-based phenotyping studies: a case study of inflammatory bowel disease comorbiditiesHealth Informatics via Machine Learning for the Clinical Management of PatientsA Decompositional Approach to Executing Quality Data Model Algorithms on the i2b2 PlatformText Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health.Contribution of Electronic Medical Records to the Management of Rare Diseases.Desiderata for computable representations of electronic health records-driven phenotype algorithms.Improving a full-text search engine: the importance of negation detection and family history context to identify cases in a biomedical data warehouse.Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.Mining and Visualizing Family History Associations in the Electronic Health Record: A Case Study for Pediatric Asthma.Patient Stratification Using Electronic Health Records from a Chronic Disease Management Program.Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum DisorderRisk factor detection for heart disease by applying text analytics in electronic medical records.Large-Scale Discovery of Disease-Disease and Disease-Gene AssociationsDeveloping an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.
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Chapter 13: Mining electronic health records in the genomics era.
description
2012 nî lūn-bûn
@nan
2012 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2012年の論文
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2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Chapter 13: Mining electronic health records in the genomics era.
@ast
Chapter 13: Mining electronic health records in the genomics era.
@en
Chapter 13: Mining electronic health records in the genomics era.
@nl
type
label
Chapter 13: Mining electronic health records in the genomics era.
@ast
Chapter 13: Mining electronic health records in the genomics era.
@en
Chapter 13: Mining electronic health records in the genomics era.
@nl
prefLabel
Chapter 13: Mining electronic health records in the genomics era.
@ast
Chapter 13: Mining electronic health records in the genomics era.
@en
Chapter 13: Mining electronic health records in the genomics era.
@nl
P2860
P1476
Chapter 13: Mining electronic health records in the genomics era.
@en
P2093
Joshua C Denny
P2860
P304
P356
10.1371/JOURNAL.PCBI.1002823
P577
2012-12-27T00:00:00Z