Columbia Open Health Data, clinical concept prevalence and co-occurrence from electronic health records

[1]  George Hripcsak,et al.  Effect of vocabulary mapping for conditions on phenotype cohorts , 2018, J. Am. Medical Informatics Assoc..

[2]  Hagit Shatkay,et al.  Co-occurrence of medical conditions: Exposing patterns through probabilistic topic modeling of snomed codes , 2018, J. Biomed. Informatics.

[3]  Shahram Ebadollahi,et al.  Early detection of heart failure with varying prediction windows by structured and unstructured data in electronic health records , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[4]  K. Luyckx,et al.  Data integration of structured and unstructured sources for assigning clinical codes to patient stays , 2015, J. Am. Medical Informatics Assoc..

[5]  B. Lo Sharing clinical trial data: maximizing benefits, minimizing risk. , 2015, JAMA.

[6]  Nigam H. Shah,et al.  Building the graph of medicine from millions of clinical narratives , 2014, Scientific Data.

[7]  V. Burt,et al.  Hypertension among adults in the United States: National Health and Nutrition Examination Survey, 2011-2012. , 2013, NCHS data brief.

[8]  Cara B. Litvin,et al.  The Prevalence of Chronic Diseases and Multimorbidity in Primary Care Practice: A PPRNet Report , 2013, The Journal of the American Board of Family Medicine.

[9]  M. Ward,et al.  Estimating Disease Prevalence and Incidence Using Administrative Data: Some Assembly Required , 2013, The Journal of Rheumatology.

[10]  J. Valderas,et al.  Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity , 2013, BMC Public Health.

[11]  Dean F Sittig,et al.  Matching identifiers in electronic health records: implications for duplicate records and patient safety , 2013, BMJ quality & safety.

[12]  Cary P Gross,et al.  The importance of clinical trial data sharing: toward more open science. , 2012, Circulation. Cardiovascular quality and outcomes.

[13]  A. Jha,et al.  Meaningful use of electronic health records: the road ahead. , 2010, JAMA.

[14]  Salim Yusuf,et al.  Efficacy and safety of dabigatran compared with warfarin at different levels of international normalised ratio control for stroke prevention in atrial fibrillation: an analysis of the RE-LY trial , 2010, The Lancet.

[15]  Bradley Malin,et al.  Evaluating re-identification risks with respect to the HIPAA privacy rule , 2010, J. Am. Medical Informatics Assoc..

[16]  Xiaoyan Wang,et al.  Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study. , 2009, Journal of the American Medical Informatics Association : JAMIA.

[17]  Caroline Blaum,et al.  The Co‐Occurrence of Chronic Diseases and Geriatric Syndromes: The Health and Retirement Study , 2009, Journal of the American Geriatrics Society.

[18]  J. Tschopp,et al.  Acute lung injury and outcomes after thoracic surgery , 2009, Current opinion in anaesthesiology.

[19]  J. Carstensen,et al.  Estimating disease prevalence using a population-based administrative healthcare database , 2007, Scandinavian journal of public health.

[20]  Kathleen Bennett,et al.  Prevalence of chronic disease in the elderly based on a national pharmacy claims database. , 2006, Age and ageing.

[21]  J. Castro‐Rodriguez,et al.  Anticholinergics in the treatment of children and adults with acute asthma: a systematic review with meta-analysis , 2005, Thorax.

[22]  Russ B Altman,et al.  Extracting and characterizing gene-drug relationships from the literature. , 2004, Pharmacogenetics.

[23]  R. Gonzales,et al.  Uncomplicated Acute Bronchitis , 2000, Annals of Internal Medicine.

[24]  V Seagroatt,et al.  Use of large medical databases to study associations between diseases. , 2000, QJM : monthly journal of the Association of Physicians.

[25]  W M Brutinel,et al.  The shrinking lungs syndrome in systemic lupus erythematosus. , 2000, Mayo Clinic proceedings.

[26]  M. Bulmer,et al.  Principles of Statistics , 1968 .

[27]  A. Jemal,et al.  Cancer statistics, 2018 , 2018, CA: a cancer journal for clinicians.

[28]  Yu-Chuan Li,et al.  Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers , 2015, MedInfo.

[29]  George Hripcsak,et al.  Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study. , 2008, Journal of the American Medical Informatics Association : JAMIA.

[30]  B. Grant,et al.  Co-occurrence of DSM-IV personality disorders in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. , 2005, Comprehensive psychiatry.

[31]  George Hripcsak,et al.  Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics , 2005, AMIA.

[32]  James J. Cimino,et al.  Automated knowledge extraction from MEDLINE citations , 2000, AMIA.