Performance evaluation and generalisability of an AI algorithm for lung cancer detection
Although its utility for lung cancer screening remains highly debated, chest x-ray (CXR) remains one of the first investigations performed in the workup of suspected lung cancer. Although early detection of actionable nodules identified on CXR has generally been regarded as having a low sensitivity, improved detection rates have been reported when CXR interpretation is augmented by computer aided detection (CAD) devices, with increased accuracy measures.
The PLCO dataset provides a highly valuable CXR dataset of confirmed lung cancer cases and other abnormalities. We plan to utilise the PLCO dataset to evaluate the performance and generalisability of a comprehensive AI algorithm.
Evaluate the performance of an AI algorithm for the detection of triaging chest x-rays with findings suspicious for lung cancer and requiring further imaging.
Evaluate the performance of an AI algorithm for the detection of other abnormalities on chest x-ray.
Melissa Ryan
Leslie Cass