In the study, a system using machine learning and natural language processing analyzed nearly 9,000 narrative CT radiology reports. The technology was able to detect and triage high-risk pulmonary nodules in the text of the reports with over 90 percent precision.
“This approach promises to improve healthcare quality by increasing the rate of appropriate lung nodule incidental finding follow-up and treatment without excessive labor or risking overutilization,” the study’s authors wrote.
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