Unstructured clinical notes contain a huge amount of information. We investigated the possibility of harvesting such information through an NLP-based approach. A manually curated ontology is the only resource required to handle all the steps of the process leading from clinical narrative to a structured data warehouse (i2b2). We have tested our approach at the Papa Giovanni XXIII hospital in Bergamo (Italy) on pathology reports collected since 2008.

Ontology-driven real world evidence extraction from clinical narratives

Chiudinelli L.;Gabetta M.;Centorrino G.;Viani N.;Tasca C.;Zambelli A.;Bucalo M.;Barbarini N.;Bellazzi R.;Sacchi L.
2019-01-01

Abstract

Unstructured clinical notes contain a huge amount of information. We investigated the possibility of harvesting such information through an NLP-based approach. A manually curated ontology is the only resource required to handle all the steps of the process leading from clinical narrative to a structured data warehouse (i2b2). We have tested our approach at the Papa Giovanni XXIII hospital in Bergamo (Italy) on pathology reports collected since 2008.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1349268
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