Using UMLS to construct a generalized hierarchical concept-based dictionary of brain functions for information extraction from the fMRI literature.
With a rapid progress in the field, a great many fMRI studies are published every year, to the extent that it is now becoming difficult for researchers to keep up with the literature, since reading papers is extremely time-consuming and labor-intensive. Thus, automatic information extraction has become an important issue. In this study, we used the Unified Medical Language System (UMLS) to construct a hierarchical concept-based dictionary of brain functions. To the best of our knowledge, this is the first generalized dictionary of this kind. We also developed an information extraction system for recognizing, mapping and classifying terms relevant to human brain study. The precision and recall of our system was on a par with that of human experts in term recognition, term mapping and term classification. Our approach presented in this paper presents an alternative to the more laborious, manual entry approach to information extraction.
Hsiao
Mei-Yu
MY
Interdisciplinary MRI/MRS Laboratory, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
Chen
Chien-Chung
CC
Chen
Jyh-Horng
JH
D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004018:Dictionaries, Medical as Topic; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008490:Medical Informatics / Q000379:methods*; D008959:Models, Neurological; D009323:Natural Language Processing; D009626:Terminology as Topic; D017432:Unified Medical Language System