Identification of Incidental Pulmonary Nodules in Free-text Radiology Reports: An Initial Investigation.
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.
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Lucas
L
Oliveira
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Ranjith
R
Tellis
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Yuechen
Y
Qian
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Karen
K
Trovato
Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Gabe
G
Mankovich
D057225:Data Mining / Q000379:methods; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D007087:Illinois / Q000453:epidemiology; D033162:Incidental Findings; D000069550:Machine Learning; D009323:Natural Language Processing; D010865:Pilot Projects; D011860:Radiography, Abdominal / Q000145:classification / Q000706:statistics & numerical data*; D011873:Radiology Information Systems / Q000145:classification / Q000600:supply & distribution*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D009626:Terminology as Topic; D018875:Vocabulary, Controlled