title: Automatic identification and classification of surgical margin status from pathology reports following prostate cancer surgery.
abstract: Prostate cancer removal surgeries result in tumor found at the surgical margin, otherwise known as a positive surgical margin, have a significantly higher chance of biochemical recurrence and clinical progression. To support clinical outcomes assessment a system was designed to automatically identify, extract, and classify key phrases from pathology reports describing this outcome. Heuristics and boundary detection were used to extract phrases. Phrases were then classified using support vector machines into one of three classes: 'positive (involved) margins,' 'negative (uninvolved) margins,' and 'not-applicable or definitive.' A total of 851 key phrases were extracted from a sample of 782 reports produced between 1996 and 2006 from two major hospitals. Despite differences in reporting style, at least 1 sentence containing a diagnosis was extracted from 780 of the 782 reports (99.74%). Of the 851 sentences extracted, 97.3% contained diagnoses. Overall accuracy of automated classification of extracted sentences into the three categories was 97.18%.
authors.affiliation: Medical Imaging Informatics Group, University of California, Los Angeles, CA 90024, USA.
authors.forename: Leonard W
authors.initials: LW
authors.lastname: D'Avolio
authors.forename: Mark S
authors.initials: MS
authors.lastname: Litwin
authors.forename: Selwyn O
authors.initials: SO
authors.lastname: Rogers
authors.forename: Alex A T
authors.initials: AA
authors.lastname: Bui
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D008297:Male; D010865:Pilot Projects; D011467:Prostate / Q000473:pathology / Q000601:surgery; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery