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resources:ohdsi_symposium_2016_posters [2016/10/19 12:32] shams.bayzid_gmail.com |
resources:ohdsi_symposium_2016_posters [2016/10/27 20:35] maura_beaton |
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===== Posters: ===== | ===== Posters: ===== | ||
- | * {{:resources:ohdsi_2016_csccs_james_weaver.pdf|Evaluating the Comparative Self-Controlled Case Series Method}} | + | Observational Data Management |
- | * {{:resources:ohdsionfhir_gatech_v1.pdf|OHDSI on FHIR Platform Development with OMOP CDM Mapping to FHIR Resources}} | + | * 1. {{:symposium_2016:mimic_cdm_ohdsi_symposium_2016.pdf|Conversion of MIMIC to OMOP CDM}} |
- | * ETL 101 Poster: {{:resources:etl_101_27.87inwide_x_40intall_.pdf|ETL 101}} | + | * 2. {{:resources:ohdsionfhir_gatech_v1.pdf|OHDSI on FHIR Platform Development with OMOP CDM Mapping to FHIR Resources}} |
- | * {{:resources:Comparative Effectiveness Research Opportunities using the OHDSI Network v6.0.pdf|Comparative Effectiveness Research Opportunities using the OHDSI Network}} | + | * 3. {{:resources:Rijnbeek_EMIF_Poster.pdf|Implementation of the OMOP CDM and OHDSI tools in the European Medical Information Framework (EMIF)}} |
- | * {{:resources:chronos_poster.pdf|CHRONOS, patient profile poster}} | + | * 4. {{:symposium_2016:poster_ohdsi_symposium_2016_auh_v2_3_.pdf|Automatic Mapping of Drug Concepts to the RxNorm Vocabulary}} |
- | * Comparing lagged linear methods for uncovering associations in EHR data: {{:symposium_2016:laggedcorrelations_ohdsi_poster.pdf}} | + | * 5. {{:symposium_2016:ohdsi_gis_rmiller.pdf|OHDSI GIS: Gaia}} |
- | * {{ | + | * 6. {{: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}} |
- | * {{:resources:Rijnbeek_PLP_Poster.pdf|Best Practices for Patient-Level Prediction in OHDSI}} | + | * 7. {{:resources:ohdsi_2016_cho_natarajan.pdf|Comparison and Evaluation on Online Geocoding Services}} |
- | * {{:resources:Rijnbeek_EMIF_Poster.pdf|Implementation of the OMOP CDM and OHDSI tools in the European Medical Information | + | * 8. {{:resources:ims_odhsi_2016_poster.pdf|Assessing Data Availability for Pharmacoepidemiology Research |
- | Framework (EMIF)}} | + | in 3 US Healthcare Databases Using the OMOP Common Data Model}} |
- | * {{:symposium_2016:poster_ohdsi_symposium_2016_auh_v2_3_.pdf|Automatic Mapping of Drug Concepts to the RxNorm Vocabulary}} | + | * 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) |
- | * {{: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}} | + | |
- | * {{:resources:using_ohdsi_tools_makadia_forlenza_v3.pdf|}}|Using OHDSI tools for clinical trial feasibility | + | |
- | * {{:resources:ohdsi_symposium_2016_broadsea_poster.pdf|BROADSEA - Docker Containers For Cross-Platform Installation of OHDSI Tools}} | + | |
- | * {{: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}} | + | |
- | * {{:symposium_2016:ohdsi_gis_rmiller.pdf|OHDSI GIS: Gaia}} | + | |
- | * {{:symposium_2016:ohdsi_symposium_2016_poster_hsu.pdf|Scalable Cohort Construction}} | + | |
- | * {{:symposium_2016:code_generator_sungjae.pdf|A web based integrated code generating system for cohort analysis}} | + | |
- | * {{: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}} | + | |
- | * {{: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}} | + | |
- | * {{:resources:ohdsi_2016_cho_natarajan.pdf|Comparison and Evaluation on Online Geocoding Services}} | + | |
- | * {{:resources:ims_odhsi_2016_poster.pdf|Assessing Data Availability for Pharmacoepidemiology Research | + | |
- | in 3 US Healthcare Databases Using the OMOP Common Data Model | + | |
}} | }} | ||
- | * {{:resources:ohdsi_2016_fdefalco_architectural_considerations.pptx|Architectural Considerations to Enable Large Scale Analytics from the OHDSI Web Platform}} | + | |
- | * {{:resources:ohdsi_2016_MIMIC_causal_benchmark_ver_for_print.pdf|An Open Benchmark for Causal Inference Using the MIMIC-III and Philips Datasets}} | + | |
- | * {{:resources:poster_rohit_updated.pdf|Learning Effective Clinical Treatment Pathways from Observational Data}} | + | Methodological Research |
- | * {{:resources:doseform-poster-v04.pdf|Analysis of drug use by dose form in large healthcare databases: Data granularity issues and CDM considerations (Huser V) | + | * 1. {{:resources:ohdsi_2016_csccs_james_weaver.pdf|Evaluating the Comparative Self-Controlled Case Series Method}} |
- | }} | + | * 2. Comparing lagged linear methods for uncovering associations in EHR data: {{:symposium_2016:laggedcorrelations_ohdsi_poster.pdf}} |
- | * {{:symposium_2016:large_scale_analysis_presented.pdf|Utilizing the OHDSI collaborative network for large-scale prognostic model validation}} | + | * 3. {{:resources:Rijnbeek_PLP_Poster.pdf|Best Practices for Patient-Level Prediction in OHDSI}} |
- | * {{:symposium_2016:oa_poster_final.pdf|A framework to efficiently identify potential prognostic factors}} | + | * 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. {{: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 | ||
+ | * 1. {{:resources:chronos_poster.pdf|CHRONOS, patient profile poster}} | ||
+ | * 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 | ||
+ | * 1. {{:resources:Comparative Effectiveness Research Opportunities using the OHDSI Network v6.0.pdf|Comparative Effectiveness Research Opportunities using the OHDSI Network}} | ||
+ | * 2. {{:resources:using_ohdsi_tools_makadia_forlenza_v3.pdf|}}|Using OHDSI tools for clinical trial feasibility | ||
+ | * 3. {{:resources:poster_rohit_updated.pdf|Learning Effective Clinical Treatment Pathways from Observational Data}} | ||
+ | * 4. {{:symposium_2016:ohdsi_sca_2016_ver1.2.pdf|A descriptive study on sudden cardiac arrest based on OMOP CDM in Korea}} | ||
+ |