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resources:ohdsi_symposium_2016_posters

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resources:ohdsi_symposium_2016_posters [2016/10/27 19:57] – maura_beatonresources:ohdsi_symposium_2016_posters [2016/11/28 22:16] (current) – maura_beaton
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 Observational Data Management Observational Data Management
   * 1. {{:symposium_2016:mimic_cdm_ohdsi_symposium_2016.pdf|Conversion of MIMIC to OMOP CDM}}   * 1. {{:symposium_2016:mimic_cdm_ohdsi_symposium_2016.pdf|Conversion of MIMIC to OMOP CDM}}
-  * 3. {{:resources:ohdsionfhir_gatech_v1.pdf|OHDSI on FHIR Platform Development with OMOP CDM Mapping to FHIR Resources}} +  * 2. {{:resources:ohdsionfhir_gatech_v1.pdf|OHDSI on FHIR Platform Development with OMOP CDM Mapping to FHIR Resources}} 
-  * 8. {{:resources:Rijnbeek_EMIF_Poster.pdf|Implementation of the OMOP CDM and OHDSI tools in the European Medical Information Framework (EMIF)}} +  * 3. {{:resources:Rijnbeek_EMIF_Poster.pdf|Implementation of the OMOP CDM and OHDSI tools in the European Medical Information Framework (EMIF)}} 
-  * 9. {{:symposium_2016:poster_ohdsi_symposium_2016_auh_v2_3_.pdf|Automatic Mapping of Drug Concepts to the RxNorm Vocabulary}}+  * 4. {{:symposium_2016:poster_ohdsi_symposium_2016_auh_v2_3_.pdf|Automatic Mapping of Drug Concepts to the RxNorm Vocabulary}} 
 +  * 5. {{:symposium_2016:ohdsi_gis_rmiller.pdf|OHDSI GIS: Gaia}} 
 +  * 6. BEST POSTER: {{:symposium_2016:transforming_the_2.33m-patient_medicare_synthetic_public_use_files_to_the_omop_cdmv5_-_etl-cms_software_and_processed_data_available_and_feature-complete.pdf|Transforming the 2.33M-patient Medicare synthetic public use files to the OMOP CDMv5: ETL-CMS software and processed data available and feature-complete}} 
 +  * 7. {{:resources:ohdsi_2016_cho_natarajan.pdf|Comparison and Evaluation on Online Geocoding Services}} 
 +  * 8. {{:resources:ims_odhsi_2016_poster.pdf|Assessing Data Availability for Pharmacoepidemiology Research  
 +in 3 US Healthcare Databases Using the OMOP Common Data Model}} 
 +  * 9. {{:resources:doseform-poster-v04.pdf|Analysis of drug use by dose form in large healthcare databases: Data granularity issues and CDM considerations (Huser V) 
 +}}
  
  
 Methodological Research Methodological Research
-  * 2. {{:resources:ohdsi_2016_csccs_james_weaver.pdf|Evaluating the Comparative Self-Controlled Case Series Method}} +  * 1. {{:resources:ohdsi_2016_csccs_james_weaver.pdf|Evaluating the Comparative Self-Controlled Case Series Method}} 
-  * 6. Comparing lagged linear methods for uncovering associations in EHR data: {{:symposium_2016:laggedcorrelations_ohdsi_poster.pdf}} +  * 2. Comparing lagged linear methods for uncovering associations in EHR data: {{:symposium_2016:laggedcorrelations_ohdsi_poster.pdf}} 
-  * 7. {{:resources:Rijnbeek_PLP_Poster.pdf|Best Practices for Patient-Level Prediction in OHDSI}} +  * 3. {{:resources:Rijnbeek_PLP_Poster.pdf|Best Practices for Patient-Level Prediction in OHDSI}} 
- +  * 4. {{:resources:ohdsi_symposium_2016_yahi_final.pdf|Natural Language Processing in Clinical and Translational Research: Of the Importance of Section Headers for Accurate Modifiers Assignments}} 
 +  * 5. {{:symposium_2016:ohdsi_symposium_2016_poster_hsu.pdf|Scalable Cohort Construction}} 
 +  * 6. BEST POSTER: {{:symposium_2016:local_control_for_bias_correction_of_time-to-event_observational_studies.pdf|Local Control for bias correction of time-to-event observational studies}} 
 +  * 7. {{:resources:ohdsi_2016_MIMIC_causal_benchmark_ver_for_print.pdf|An Open Benchmark for Causal Inference Using the MIMIC-III and Philips Datasets}} 
 +  * 8. {{:symposium_2016:large_scale_analysis_presented.pdf|Utilizing the OHDSI collaborative network for large-scale prognostic model validation}} 
 +  * 9. {{:symposium_2016:oa_poster_final.pdf|A framework to efficiently identify potential prognostic factors}} 
 + 
      
  
 Analytics, Technology and Infrastructure Analytics, Technology and Infrastructure
-  * 5. {{:resources:chronos_poster.pdf|CHRONOS, patient profile poster}} +  * 1. BEST POSTER: {{:resources:chronos_poster.pdf|CHRONOS, patient profile poster}} 
-  * 10.{{:symposium_2016:mobile_health_iphone_app_for_precision_medicine_alzheimer_s_research_using_omop_cdm.pdf|Mobile Health iPhone App for Precision Medicine Alzheimer's Research Using OMOP CDM}}+  * 2.{{:symposium_2016:mobile_health_iphone_app_for_precision_medicine_alzheimer_s_research_using_omop_cdm.pdf|Mobile Health iPhone App for Precision Medicine Alzheimer's Research Using OMOP CDM}} 
 +  * 3. {{:resources:ohdsi_symposium_2016_broadsea_poster.pdf|BROADSEA - Docker Containers For Cross-Platform Installation of OHDSI Tools}} 
 +  * 4. {{:symposium_2016:code_generator_sungjae.pdf|A web based integrated code generating system for cohort analysis}} 
 +  * 5. {{:symposium_2016:ohdsi_2016_fdefalco_architectural_considerations.pdf|Architectural Considerations to Enable Large Scale Analytics from the OHDSI Web Platform }}  
  
 Clinical Applications: Clinical Characterization Clinical Applications: Clinical Characterization
-  * 4. {{:resources:Comparative Effectiveness Research Opportunities using the OHDSI Network v6.0.pdf|Comparative Effectiveness Research Opportunities using the OHDSI Network}} +  * 1. {{:resources:Comparative Effectiveness Research Opportunities using the OHDSI Network v6.0.pdf|Comparative Effectiveness Research Opportunities using the OHDSI Network}} 
-  * 11. {{:resources:using_ohdsi_tools_makadia_forlenza_v3.pdf|}}|Using OHDSI tools for clinical trial feasibility +  * 2. BEST POSTER: {{:resources:using_ohdsi_tools_makadia_forlenza_v3.pdf|}}|Using OHDSI tools for clinical trial feasibility 
-  * 12. {{:resources:ohdsi_symposium_2016_broadsea_poster.pdf|BROADSEA - Docker Containers For Cross-Platform Installation of OHDSI Tools}} +  * 3. {{:resources:poster_rohit_updated.pdf|Learning Effective Clinical Treatment Pathways from Observational Data}} 
-  * 13. {{:resources:ohdsi_symposium_2016_yahi_final.pdf|Natural Language Processing in Clinical and Translational Research: Of the Importance of Section Headers for Accurate Modifiers Assignments}} +  * 4. {{:symposium_2016:ohdsi_sca_2016_ver1.2.pdf|A descriptive study on sudden cardiac arrest based on OMOP CDM in Korea}} 
-  * 14. {{:symposium_2016:ohdsi_gis_rmiller.pdf|OHDSI GIS: Gaia}} + 
-  * 15. {{:symposium_2016:ohdsi_symposium_2016_poster_hsu.pdf|Scalable Cohort Construction}} +
-  * 16. {{:symposium_2016:code_generator_sungjae.pdf|A web based integrated code generating system for cohort analysis}} +
-  * 17. {{:symposium_2016:local_control_for_bias_correction_of_time-to-event_observational_studies.pdf|Local Control for bias correction of time-to-event observational studies}} +
-  * 18. {{:symposium_2016:transforming_the_2.33m-patient_medicare_synthetic_public_use_files_to_the_omop_cdmv5_-_etl-cms_software_and_processed_data_available_and_feature-complete.pdf|Transforming the 2.33M-patient Medicare synthetic public use files to the OMOP CDMv5: ETL-CMS software and processed data available and feature-complete}} +
-  * 19. {{:resources:ohdsi_2016_cho_natarajan.pdf|Comparison and Evaluation on Online Geocoding Services}} +
-  * 20. {{:resources:ims_odhsi_2016_poster.pdf|Assessing Data Availability for Pharmacoepidemiology Research  +
-in 3 US Healthcare Databases Using the OMOP Common Data Model +
-}} +
-  * 21. {{:symposium_2016:ohdsi_2016_fdefalco_architectural_considerations.pdf|Architectural Considerations to Enable Large Scale Analytics from the OHDSI Web Platform }}  +
-  * 22. {{:resources:ohdsi_2016_MIMIC_causal_benchmark_ver_for_print.pdf|An Open Benchmark for Causal Inference Using the MIMIC-III and Philips Datasets}} +
-  * 23. {{:resources:poster_rohit_updated.pdf|Learning Effective Clinical Treatment Pathways from Observational Data}} +
-  * 24. {{:resources:doseform-poster-v04.pdf|Analysis of drug use by dose form in large healthcare databases: Data granularity issues and CDM considerations (Huser V) +
-}} +
-  * 25. {{:symposium_2016:large_scale_analysis_presented.pdf|Utilizing the OHDSI collaborative network for large-scale prognostic model validation}} +
-  * 26. {{:symposium_2016:oa_poster_final.pdf|A framework to efficiently identify potential prognostic factors}} +
-  * 27. {{:symposium_2016:ohdsi_sca_2016_ver1.2.pdf|A descriptive study on sudden cardiac arrest based on OMOP CDM in Korea}}+
  
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