Electronic medical records for discovery research in rheumatoid arthritis. - Wikidata - awgldk - TriplyDB

Electronic medical records for discovery research in rheumatoid arthritis.

Electronic medical records for discovery research in rheumatoid arthritis.

http://www.wikidata.org/entity/Q35062205

about

SHRINE: enabling nationally scalable multi-site disease studies Approaches to canine health surveillance Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project Extracting information from the text of electronic medical records to improve case detection: a systematic review Coreference resolution: a review of general methodologies and applications in the clinical domain Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits What evidence is there for a delay in diagnostic coding of RA in UK general practice records? An observational study of free text Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources An eMERGE Clinical Center at Partners Personalized Medicine Extracting research-quality phenotypes from electronic health records to support precision medicine Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts Genetics and cardiovascular disease: a policy statement from the American Heart Association.Feasibility of studying brain morphology in major depressive disorder with structural magnetic resonance imaging and clinical data from the electronic medical record: a pilot study.An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data Applying active learning to high-throughput phenotyping algorithms for electronic health records data Identification of Nonresponse to Treatment Using Narrative Data in an Electronic Health Record Inflammatory Bowel Disease Cohort.Case definitions in Swedish register data to identify systemic lupus erythematosus.Learning statistical models of phenotypes using noisy labeled training data.Retrospective cohort study of anti-tumor necrosis factor agent use in a veteran population Lipid and lipoprotein levels and trend in rheumatoid arthritis compared to the general population.Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.Probabilistic techniques for obtaining accurate patient counts in Clinical Data Warehouses.Mortality and extraintestinal cancers in patients with primary sclerosing cholangitis and inflammatory bowel disease.Automatic lymphoma classification with sentence subgraph mining from pathology reports.Influenza detection from emergency department reports using natural language processing and Bayesian network classifiers Impact of data fragmentation across healthcare centers on the accuracy of a high-throughput clinical phenotyping algorithm for specifying subjects with type 2 diabetes mellitus The co-morbidity burden of children and young adults with autism spectrum disorders Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records.The absence of longitudinal data limits the accuracy of high-throughput clinical phenotyping for identifying type 2 diabetes mellitus subjects Toward personalizing treatment for depression: predicting diagnosis and severity.Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records.Chapter 13: Mining electronic health records in the genomics era.Graph-based signal integration for high-throughput phenotyping.Discovering peripheral arterial disease cases from radiology notes using natural language processing.Optimising use of electronic health records to describe the presentation of rheumatoid arthritis in primary care: a strategy for developing code lists Improving sensitivity of machine learning methods for automated case identification from free-text electronic medical records Optimising the use of electronic health records to estimate the incidence of rheumatoid arthritis in primary care: what information is hidden in free text?Improved de-identification of physician notes through integrative modeling of both public and private medical text.

P2860

Q24288701-926EACAC-BB25-4758-856F-3440207186F4 Q24288900-D41F1CA5-2760-4D81-AF18-F63A47E0EED8 Q24658467-0A62120B-4099-4B7D-9DC5-6AD45D584C48 Q26766556-9127ED70-2AA1-4689-A263-9115E3467931 Q27014480-246CB618-6CFA-4270-B20F-5171595D3E24 Q28394008-20DA9155-4555-4414-84FF-C9532206B05C Q28545832-C773488B-421D-4843-A97F-072A2561C2F8 Q28596818-12EA1775-47BD-421C-A21A-CAA8B0B92926 Q28597791-C80A1590-0178-4962-904A-CC838A7BFC7D Q28601813-00AC016D-D7B1-41E7-9E88-009D20C63FFB Q28648163-57D87E09-9453-4ECA-83E8-16BF471D8007 Q29126350-C303CE94-4D33-4D83-A9F5-BCBB171FBD7C Q30418104-E79E052F-0627-40A1-970B-5BFDD4821765 Q30577346-064455EE-AA3C-4A24-976B-5A4AAAF7D7DE Q30585475-B1ACD0F8-B450-416F-AF10-256B676D5E23 Q30653374-8F91D8A8-06B0-46ED-84DB-E772F6D29648 Q30655146-01C4ED76-1D22-4488-AB7E-5EEBA4A9205F Q30991140-ED6BE511-B5F7-404D-A09F-20500CDD313C Q31034949-0443D214-B373-4C62-809A-B5C839070433 Q31095809-1A1076DF-02EA-4109-B688-DFA6A9E71342 Q33667897-22FD3090-312E-4739-B553-ED31B3543820 Q33765761-A1DDE41D-3DF7-4271-BC18-2F3A886AC495 Q33823314-B86E9D24-E53C-4EB2-98FF-BBC9B3513BC2 Q34045694-4AF88523-7E29-4122-BC3D-CD792556CFCE Q34062402-2841EFBD-2703-449D-9F9B-0FD10024E9E7 Q34101867-CD301FCE-ADB0-4B51-8697-22DC4D881C61 Q34101954-F24036B2-291B-4A49-971A-777472C23D33 Q34129068-A6EF16A6-BD16-47C8-8299-833E755F5EEF Q34236692-28D9E2CF-A4AA-4BBC-8B35-6A62C482B388 Q34289324-8B43ACA6-0F9A-4297-B363-27635A2029E2 Q34326946-1251DDD1-5AFD-4932-89BB-3C41DFE90D81 Q34430123-2BEE3B0B-0AFE-4275-B69E-61C2FFC32FC5 Q34458840-D0EB56A3-F35E-4C7E-A0A0-7DB670850111 Q34539676-950F7FC0-B46C-46E4-9FB6-3FDBF8A8930B Q34548806-138C5306-A289-41A8-9AA3-B9F527655CE5 Q34583712-9ECFA695-0948-4A7F-AEAC-0723FC984960 Q34602211-9C933987-D900-4986-9E27-B9C779F4A792 Q34604277-9972E07A-5B0B-4E2A-BBAE-0720782DF2FB Q34960488-1D6A9035-2EAA-45E8-B5B7-0A0190EA594F Q35003628-8DFF6E97-B68A-4048-804E-A3C9BAAC32E4

P2860

Electronic medical records for discovery research in rheumatoid arthritis.

http://www.wikidata.org/entity/Q35062205

description

2010 nî lūn-bûn

@nan

2010 թուականի Օգոստոսին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի օգոստոսին հրատարակված գիտական հոդված

@hy

2010年の論文

@ja

2010年論文

@yue

2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

@zh-mo

2010年論文

@zh-tw

2010年论文

@wuu

name

Electronic medical records for discovery research in rheumatoid arthritis.

@ast

Electronic medical records for discovery research in rheumatoid arthritis.

@en

type

label

Electronic medical records for discovery research in rheumatoid arthritis.

@ast

Electronic medical records for discovery research in rheumatoid arthritis.

@en

prefLabel

Electronic medical records for discovery research in rheumatoid arthritis.

@ast

Electronic medical records for discovery research in rheumatoid arthritis.

@en

P1433

Q35062205-303EA180-5BF0-477D-BE81-4155BD1AD651

P1476

Q35062205-0B033E5B-BD23-4C63-BCA8-3A71672BFD5A

P2093

Q35062205-13C57541-F9E3-4232-9A32-D01426229295

Q35062205-1B18FDB1-4E10-40C1-99E7-327AFE0B3661

Q35062205-1BEA0824-971C-413D-80A9-262BDAC81B39

Q35062205-24FC1BB7-949A-4D87-89F1-DC8146A8A55A

Q35062205-46F6487E-E2CA-49C6-98F7-D66E4BABA471

Q35062205-4FC257F0-C856-4ADD-A934-1DC790F6AA96

Q35062205-61221D0E-DEA8-403A-9ED4-73B118F9F76C

Q35062205-AC26A668-B51F-41D1-AB84-5F1035BFE74F

Q35062205-ADD99279-89A6-4F98-A0A3-0D426FFE80AD

Q35062205-C799C1DA-FC75-4CAD-B682-F97444D795F8

P2860

Q35062205-130EFE67-A663-4A06-9B5C-42BCB8B5459E

Q35062205-1445F3A5-3E74-4890-A349-AB4F7D0658F5

Q35062205-189B3B33-BEAC-49BD-B293-AF56500D94C0

Q35062205-18BA6F35-8744-4310-B3BA-D4ECEFAA9432

Q35062205-21E50462-E156-4F52-8046-885F29CA9A0E

Q35062205-27684E25-A566-442F-B552-9DB88CF0CCC7

Q35062205-38077776-A418-44BF-9005-3CFBADF00E69

Q35062205-76FAC7BB-F2B5-4A87-ACC6-5D0E86033DB1

Q35062205-870D5E5D-BAA6-4D52-83E7-26FF98EAB4CE

Q35062205-8B51102B-F064-4666-A061-7E084065555A

P304

Q35062205-41BE5E75-B2DF-45D7-9B08-DA171A1E07D5

P31

Q35062205-894C63AD-7E71-4F64-B77D-8AA8D5D647E8

P356

Q35062205-319E1801-EC6F-47BF-8679-5AE6621FADDE

P433

Q35062205-93F7F495-A385-4F2E-816C-4659FCDD7AEA

P478

Q35062205-A231E623-D120-4B34-98B4-A1824E67EF1E

P50

Q35062205-A5BF2C13-5C8B-46A7-BECD-7D66AE6B4A37

Q35062205-DF98E8C6-3611-447D-855F-0C0A1B7ECC83

P577

Q35062205-7908EA6D-7D17-4EF9-9618-D7F61AF32BBA

P5875

Q35062205-969241AF-01D3-4F50-B854-469C4785F781

P698

Q35062205-8A70425B-A381-4393-88EB-3C0DECD193D3

P932

Q35062205-D563029E-952E-4E50-9286-BDE541375032

P356

P1433

Arthritis Care and Research

P1476

Electronic medical records for discovery research in rheumatoid arthritis.

@en

P2093

Elizabeth W Karlson

http://www.w3.org/2001/XMLSchema#string

Katherine P Liao

http://www.w3.org/2001/XMLSchema#string

Qing Zeng-treitler

http://www.w3.org/2001/XMLSchema#string

Robert M Plenge

http://www.w3.org/2001/XMLSchema#string

Sergey Goryachev

http://www.w3.org/2001/XMLSchema#string

Shawn Murphy

http://www.w3.org/2001/XMLSchema#string

Soumya Raychaudhuri

http://www.w3.org/2001/XMLSchema#string

Susanne Churchill

http://www.w3.org/2001/XMLSchema#string

Tianxi Cai

http://www.w3.org/2001/XMLSchema#string

Vivian Gainer

http://www.w3.org/2001/XMLSchema#string

P2860

Assessing the level of healthcare information technology adoption in the United States: a snapshot

The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis

Will the wave finally break? A brief view of the adoption of electronic medical records in the United States.

Accuracy of Medicare claims data for rheumatologic diagnoses in total hip replacement recipients.

Automated identification of acute hepatitis B using electronic medical record data to facilitate public health surveillance

Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system.

Electronic Support for Public Health: validated case finding and reporting for notifiable diseases using electronic medical data.

Association of methotrexate and tumour necrosis factor antagonists with risk of infectious outcomes including opportunistic infections in the CORRONA registry.

Detecting adverse events using information technology

Electronic health records in ambulatory care--a national survey of physicians.

P304

1120-1127

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1002/ACR.20184

http://www.w3.org/2001/XMLSchema#string

P433

8

http://www.w3.org/2001/XMLSchema#string

P478

62

http://www.w3.org/2001/XMLSchema#string

P50

Peter Szolovits

P577

2010-08-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

42110270

http://www.w3.org/2001/XMLSchema#string

P698

20235204

http://www.w3.org/2001/XMLSchema#string

P932

3121049

http://www.w3.org/2001/XMLSchema#string