Digirolamo Lab

Research focus

NIH R01 · 2024

Increasing Nodule Detection in Lung Cancer by Non-Conscious Detection of "Missed" Nodules and Machine Learning

Lung cancer has a 5-year survival rate of 21% and more than 80% of all new patients are diagnosed at an advanced stage. Finding small lung nodules representing the early stages of lung cancer are critical, but diagnostic error can be as high as 50% in harder-to-detect lung nodules. Nodule detection is the outcome of a difficult search task which employs both conscious and non-conscious brain processes that radiologists spend years of training enhancing. Currently, detection is constrained to those processes that become conscious. A critical need is characterizing and utilizing these non-conscious processes to improve nodule detection beyond conscious detection limits. This proposed RO1 will…

From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.