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projects:workgroups:causal_inference

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projects:workgroups:causal_inference [2019/11/24 02:38]
abbas
projects:workgroups:causal_inference [2019/11/24 04:25] (current)
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 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. ​+CICT is a novel computational method that uses large-scale health data to predict potential causal relationships between clinical conditions. 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. ​
  
 *** Participants:​ *** *** Participants:​ ***
projects/workgroups/causal_inference.txt ยท Last modified: 2019/11/24 04:25 by abbas