CT-Based Deep Learning Model May Reduce False Positives with Indeterminate Lung Nodules by Nearly 40 Percent

In a recent interview with Diagnostic Imaging, Noa Antonissen, M.D., and Colin Jacobs, Ph.D., discussed new research findings demonstrating robust risk stratification with a CT-based deep learning model for lung nodules as well as a 39.4 percent reduction in false positives in comparison to traditional classification.

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