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projects:workgroups:causal_inference

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projects:workgroups:causal_inference [2019/11/24 02:33]
abbas
projects:workgroups:causal_inference [2019/11/24 02:38]
abbas
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-CICT is a novel computational method that uses large-scale health data to predict potential causal relationships ​ between clinical conditions, genes, proteins and other interacting factors. A pipeline for epidemiological etiological inference is also developed to validate the results of CICT. CICT and the validation pipeline have been used by different teams to identify latent risk factor ​and unknown effects of clinical conditions or procedures, which resulted in reporting of multiple novel findings during 2018-2019. Two large-scale population-level claims datasets from HCUP California and Florida have been used for discovery and validation. OHDSI will be used to empower the engine for the new phase. ​+CICT is a novel computational method that uses large-scale health data to predict potential causal relationships between clinical conditions, genes, proteinsand other interacting factors. A pipeline for epidemiological etiological inference is also developed to validate the results of CICT. CICT and the validation pipeline have been used by different teams to identify latent risk factors ​and unknown effects of clinical conditions or procedures, which resulted in reporting of multiple novel findings during 2018-2019. Two large-scale population-level claims datasets from HCUP California and Florida have been used for discovery and validation. OHDSI will be used to empower the engine for the new phase. ​
  
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projects/workgroups/causal_inference.txt ยท Last modified: 2020/01/01 02:36 by abbas