Structuring of free-text diagnostic report.
OBJECTIVE
It is useful to convert free-text diagnostic reports into structured diagnostic reports by semantic analysis for the secondary investigation of their contents. In this study, we propose a system in which description units are automatically extracted to create structured text reports and we evaluated its usefulness.


METHODS
We defined the rules to create description units and developed the system that can automatically extract these description units from free-text diagnostic reports. We applied this system to reports of cerebral perfusion scintigrams and obtained 5 dictionaries of description units, increasing the number of scintigrams from 100 to 500 in increments of 100. Each dictionary was used to analyze another 100 scintigrams. The results obtained using each dictionary were compared with the results of physicians' interpretation.


RESULTS
The recall rate of this system to the physicians' interpretation increased when correlated with the number of scintigrams but with 300 cases was almost saturated at 85%.


CONCLUSIONS
We propose a semantic analysis system and show its usefulness in the semantic evaluation of the reports of cerebral perfusion scintigrams.
Fujii
Hirofumi
H
Functional Imaging Division, Research Center for Innovative Oncology, National Cancer Center Hospital East, Kashiwa, Japan. hifujii@east.ncc.go.jp
Yamagishi
Hiromasa
H
Ando
Yutaka
Y
Tsukamoto
Nobuhiro
N
Kawaguchi
Osamu
O
Kasamatsu
Tomotaka
T
Kurosaki
Kaoru
K
Osada
Masakazu
M
Kaneko
Hiroshi
H
Kubo
Atsushi
A
D000544:Alzheimer Disease / Q000000981:diagnostic imaging*; D002560:Cerebrovascular Circulation; D054022:Cerebrum / Q000098:blood supply / Q000000981:diagnostic imaging*; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D011873:Radiology Information Systems; D011875:Radionuclide Angiography