A Field Theoretical Approach to Medical Natural Language Processing

• Published in: IEEE transactions on information technology in biomedicine Vol. 11; no. 4; pp. 364 - 375
• Main Authors: Taira, R.K., Bashyam, V., Kangarloo, H.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2007
• Subjects: Calibration; Chemistry; Energy states; Information Storage and Retrieval - methods; Information systems; Information Theory; Knowledge representation; Linguistics; Medical; Medical Informatics - methods; Medical Records Systems, Computerized; Natural Language Processing; natural language processing (NLP); Parsers; Physics; Potential energy; Psychology; Radiology; Sentences; Statistics; structured medical reporting; System testing; Terminology as Topic; Texts; Vocabulary, Controlled
• ISSN: 1089-7771; 1558-0032
• DOI: 10.1109/TITB.2006.884368

A parser for medical free text reports has been developed that is based on a chemistry/physics inspired ldquofield theoryrdquo for word-word sentence-level dependencies. The transition from the linguistic world to the world of interacting particles with potential energies is guided by a psycholinguistics thought experiment related to the amount of ldquoworkrdquo required to bring a reference word into an anchored configuration of words. Calibration experiments involving four and five grams were conducted. Data from these experiments were used as a knowledge source for estimating field conditions for words in sentences sampled from a corpus of medical reports. The result of the parser is a dependency tree that represents the global minimum energy state of the system of words for a given sentence. The system was trained and tested on a corpus of radiology reports. Preliminary performance, as quantified by link recall and precision statistics, is 84.9% and 89.9%, respectively.