A field theoretical approach to medical natural language processing.
A parser for medical free text reports has been developed that is based on a chemistry/physics inspired "field theory" 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 "work" 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.
Medical Imaging Informatics Group, University of California at Los Angeles, Los Angeles, CA 90024, USA . rtaira@mii.ucla.edu
Ricky K
RK
Taira
Vijayaraghavan
V
Bashyam
Hooshang
H
Kangarloo
D016247:Information Storage and Retrieval / Q000379:methods*; D007257:Information Theory; D008490:Medical Informatics / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D009626:Terminology as Topic; D018875:Vocabulary, Controlled