Abstract
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.
MeSH terms
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Data Mining / methods
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Decision Support Systems, Clinical / organization & administration*
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Diagnosis, Computer-Assisted / methods*
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Humans
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Illinois / epidemiology
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Incidental Findings
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Machine Learning*
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Natural Language Processing*
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Pilot Projects
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Radiography, Abdominal / classification
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Radiography, Abdominal / statistics & numerical data*
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Radiology Information Systems / classification
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Radiology Information Systems / supply & distribution*
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Reproducibility of Results
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Sensitivity and Specificity
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Terminology as Topic
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Vocabulary, Controlled