Rule-based Cervical Spine Defect Classification Using Medical Narratives.
Journal:
Studies in health technology and informatics
Published Date:
Jan 1, 2015
Abstract
Classifying the defects occurring at the cervical spine provides the basis for surgical treatment planning and therapy recommendation. This process requires evidence from patient records. Further, the degree of a defect needs to be encoded in a standardized from to facilitate data exchange and multimodal interoperability. In this paper, a concept for automatic defect classification based on information extracted from textual data of patient records is presented. In a retrospective study, the classifier is applied to clinical documents and the classification results are evaluated.
Authors
Keywords
Algorithms
Biological Ontologies
Cervical Vertebrae
Decision Support Systems, Clinical
Diagnosis, Computer-Assisted
Electronic Health Records
Humans
Knowledge Bases
Machine Learning
Narration
Natural Language Processing
Reproducibility of Results
Sensitivity and Specificity
Spinal Stenosis
Terminology as Topic