Development of automatic generation system for lung nodule finding descriptions.
PLoS One
; 19(3): e0300325, 2024.
Article
em En
| MEDLINE
| ID: mdl-38512860
ABSTRACT
Worldwide, lung cancer is the leading cause of cancer-related deaths. To manage lung nodules, radiologists observe computed tomography images, review various imaging findings, and record these in radiology reports. The report contents should be of high quality and uniform regardless of the radiologist. Here, we propose an artificial intelligence system that automatically generates descriptions related to lung nodules in computed tomography images. Our system consists of an image recognition method for extracting contents-namely, bronchopulmonary segments and nodule characteristics from images-and a natural language processing method to generate fluent descriptions. To verify our system's clinical usefulness, we conducted an experiment in which two radiologists created nodule descriptions of findings using our system. Through our system, the similarity of the described contents between the two radiologists (p = 0.001) and the comprehensiveness of the contents (p = 0.025) improved, while the accuracy did not significantly deteriorate (p = 0.484).
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Nódulo Pulmonar Solitário
/
Neoplasias Pulmonares
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article