[Development of the method for the similarity detection of descriptions in radiology reports using structuring technology].
Radiologists often spend much time for re-reading some of the past free-text radiology reports and determining interval changes in the physical findings when creating a report for long term cases. The aim of this study was to propose the method to detect semantic similar descriptions in the free-text reports using the structuring method based on text-mining technology. In a previous study, we had developed the structuring method that can semantically analyze the free-text reports and convert them into the description unit consisting of five items: finding/diagnosis, modifier, region, regional modifier, and confidence. Our developed prototype system extracted similar descriptions from the free-text reports by calculating the similarity index between description units. We confirmed similar descriptions extracted by the system applied to free-text reports of cases which had more than one chest CT examination written in actual clinical situation. As a result, it became available to identify candidates of similar descriptions from free-text reports. In some cases regarding practical use, the similar descriptions could not be identified in the sentences which used paraphrasing or where the findings had status changes. A solution of identifying similarity in these cases was necessary to improve the method. With the presented method here, it is expected that interval changes in the findings can be visualized and applied it to support diagnosis.
Futami
Hikaru
H
System Integration Division, Toshiba Medical Systems Corporation.
Yamagishi
Hiromasa
H
Kawaguchi
Osamu
O
Tsukamoto
Nobuhiro
N
Fujii
Hirofumi
H
Kasamatsu
Tomotaka
T
Ando
Yutaka
Y
Osada
Masakazu
M
Kubo
Atsushi
A
D009323:Natural Language Processing; D011873:Radiology Information Systems