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-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. We are now open to collaboration requests from clinical researchers who are seeking novel hypothesis and/or epidemiological evidence from population level data. We are also eager to start collaborations (individual or organizational) that bring us access to large-scale claims/EMR datasets in OHDSI.
+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.
-*** Publications and conference papers: ***
+**CICT pipeline can produce highly accurate novel hypotheses and analyses results at a fast pace. ** Accordingly, we are now open to collaboration requests from clinical researchers who are seeking novel hypotheses from data and/or epidemiological evidence from population-level data. We are also eager to start ** collaborations ** with individuals or organizations that can provide us access to large-scale claims/EMR datasets in OHDSI, based on their existing access.
-[[http://example.com|External Link]]
+*** Publications and conference papers: ***
 [[https://www.biorxiv.org/content/10.1101/439117v1|Asthma-Neoplasms Relationships: New Insights Using Machine Inference, Epidemiological Reasoning, And Big Data]]

Observational Health Data Sciences and Informatics

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