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PUBMED FOR HANDHELDS

Journal Abstract Search


207 related items for PubMed ID: 26262419

  • 21. Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages.
    Wu Y, Lei J, Wei WQ, Tang B, Denny JC, Rosenbloom ST, Miller RA, Giuse DA, Zheng K, Xu H.
    Stud Health Technol Inform; 2013; 192():662-6. PubMed ID: 23920639
    [Abstract] [Full Text] [Related]

  • 22. Extraction of adverse drug effects from clinical records.
    Aramaki E, Miura Y, Tonoike M, Ohkuma T, Masuichi H, Waki K, Ohe K.
    Stud Health Technol Inform; 2010; 160(Pt 1):739-43. PubMed ID: 20841784
    [Abstract] [Full Text] [Related]

  • 23. Design, development and first validation of a transcoding system from ICD-9-CM to ICD-10 in the IT.DRG Italian project.
    Della Mea V, Vuattolo O, Frattura L, Munari F, Verdini E, Zanier L, Arcangeli L, Carle F.
    Stud Health Technol Inform; 2015; 210():135-9. PubMed ID: 25991117
    [Abstract] [Full Text] [Related]

  • 24. Formalizing mappings to optimize automated schema alignment: application to rare diseases.
    Maaroufi M, Choquet R, Landais P, Jaulent MC.
    Stud Health Technol Inform; 2014; 205():283-7. PubMed ID: 25160191
    [Abstract] [Full Text] [Related]

  • 25. Model-based query language for analyzing clinical processes.
    Barzdins J, Barzdins J, Rencis E, Sostaks A.
    Stud Health Technol Inform; 2013; 192():1072. PubMed ID: 23920846
    [Abstract] [Full Text] [Related]

  • 26. Deterministic record linkage versus similarity functions: a study in health databases from Brazil.
    Suzuki KM, Porto Filho CH, Cozin LF, Pereyra LC, de Azevedo Marques PM.
    Stud Health Technol Inform; 2013; 192():562-6. PubMed ID: 23920618
    [Abstract] [Full Text] [Related]

  • 27. User needs and requirements analysis for big data healthcare applications.
    Zillner S, Lasierra N, Faix W, Neururer S.
    Stud Health Technol Inform; 2014; 205():657-61. PubMed ID: 25160268
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  • 28. Restructuring an EHR system and the Medical Markup Language (MML) standard to improve interoperability by archetype technology.
    Kobayashi S, Kume N, Yoshihara H.
    Stud Health Technol Inform; 2015; 216():881. PubMed ID: 26262183
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  • 31. Towards a light-weight query engine for accessing health sensor data in a fall prevention system.
    Kreiner K, Gossy C, Drobics M.
    Stud Health Technol Inform; 2014; 205():1055-9. PubMed ID: 25160350
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  • 32. Integrating personalized health information from MedlinePlus in a patient portal.
    Borbolla D, Del Fiol G, Taliercio V, Otero C, Campos F, Martinez M, Luna D, Quiros F.
    Stud Health Technol Inform; 2014; 205():348-52. PubMed ID: 25160204
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  • 33. A framework for integrating heterogeneous clinical data for a disease area into a central data warehouse.
    Karmen C, Ganzinger M, Kohl CD, Firnkorn D, Knaup-Gregori P.
    Stud Health Technol Inform; 2014; 205():1060-4. PubMed ID: 25160351
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  • 34. Is it Possible to Make Everyone Talk in the Same Language?
    Lau M, Fung V, Cheung NT, Wong A, Tam E, Wai A.
    Stud Health Technol Inform; 2015; 216():1086. PubMed ID: 26262385
    [Abstract] [Full Text] [Related]

  • 35. Big Data and Analytics in Healthcare.
    Tan SS, Gao G, Koch S.
    Methods Inf Med; 2015; 54(6):546-7. PubMed ID: 26577624
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  • 36. Interface map as a user-driven and activity-driven interoperability standards portfolio.
    Virkanen H, Mykkänen J, Tuomainen M.
    Stud Health Technol Inform; 2013; 192():407-11. PubMed ID: 23920586
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  • 39. Validating EHR documents: automatic schematron generation using archetypes.
    Pfeiffer K, Duftschmid G, Rinner C.
    Stud Health Technol Inform; 2014; 198():101-7. PubMed ID: 24825691
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  • 40. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
    Gobbel GT, Reeves R, Jayaramaraja S, Giuse D, Speroff T, Brown SH, Elkin PL, Matheny ME.
    J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
    [Abstract] [Full Text] [Related]


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