Oliveira Lucas, Tellis Ranjith, Qian Yuechen, Trovato Karen, Mankovich Gabe
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Stud Health Technol Inform. 2015;216:1027.
Advances in image quality produced by computed tomography (CT) and the growth in the number of image studies currently performed has made the management of incidental pulmonary nodules (IPNs) a challenging task. This research aims to identify IPNs in radiology reports of chest and abdominal CT by Natural Language Processing techiniques to recognize IPN in sentences of radiology reports. Our preliminary analysis indicates vastly different pulmonary incidental findings rates for two different patient groups.
计算机断层扫描(CT)产生的图像质量进步以及当前进行的图像研究数量的增长,使得偶然发现的肺结节(IPN)的管理成为一项具有挑战性的任务。本研究旨在通过自然语言处理技术在胸部和腹部CT的放射学报告中识别IPN,以在放射学报告的句子中识别IPN。我们的初步分析表明,两个不同患者组的肺部偶然发现率差异很大。