title: Complex epilepsy phenotype extraction from narrative clinical discharge summaries.
abstract: Epilepsy is a common serious neurological disorder with a complex set of possible phenotypes ranging from pathologic abnormalities to variations in electroencephalogram. This paper presents a system called Phenotype Exaction in Epilepsy (PEEP) for extracting complex epilepsy phenotypes and their correlated anatomical locations from clinical discharge summaries, a primary data source for this purpose. PEEP generates candidate phenotype and anatomical location pairs by embedding a named entity recognition method, based on the Epilepsy and Seizure Ontology, into the National Library of Medicine's MetaMap program. Such candidate pairs are further processed using a correlation algorithm. The derived phenotypes and correlated locations have been used for cohort identification with an integrated ontology-driven visual query interface. To evaluate the performance of PEEP, 400 de-identified discharge summaries were used for development and an additional 262 were used as test data. PEEP achieved a micro-averaged precision of 0.924, recall of 0.931, and F1-measure of 0.927 for extracting epilepsy phenotypes. The performance on the extraction of correlated phenotypes and anatomical locations shows a micro-averaged F1-measure of 0.856 (Precision: 0.852, Recall: 0.859). The evaluation demonstrates that PEEP is an effective approach to extracting complex epilepsy phenotypes for cohort identification.
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Licong
authors: L
authors: Cui
authors: Division of Medical Informatics, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Satya S
authors: SS
authors: Sahoo
authors: Department of Neurology, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Samden D
authors: SD
authors: Lhatoo
authors: Department of Neurology, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Gaurav
authors: G
authors: Garg
authors: Department of Neurology, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Prashant
authors: P
authors: Rai
authors: Department of Neurology, Case Western Reserve University, Cleveland, OH 44106, USA.
authors: Alireza
authors: A
authors: Bozorgi
authors: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA; Division of Medical Informatics, Case Western Reserve University, Cleveland, OH 44106, USA. Electronic address: gq@case.edu.
authors: Guo-Qiang
authors: GQ
authors: Zhang
mesh_terms: D001185:Artificial Intelligence; D064229:Biological Ontologies; D057225:Data Mining / Q000379:methods; D004569:Electroencephalography / Q000145:classification*; D004827:Epilepsy / Q000145:classification* / Q000175:diagnosis*; D055991:Health Records, Personal; D006801:Humans; D009323:Natural Language Processing; D063886:Patient Discharge Summaries / Q000145:classification*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010641:Phenotype; D012660:Semantics
keywords: Cohort identification; Epilepsy; Information extraction