Traditionally, physicians use CT scans to assess lung nodules, which can lead to earlier cancer diagnoses. However, this approach can also lead to overtreatment if nodules are benign.
Researchers developed the algorithm to assess cancer risk based on data on 15,693 lung nodules from the National Lung Screening Trial, Nashville, Tenn.-based Vanderbilt University Medical Center and Oxford University Hospitals.
Researchers found the algorithm was linked to a higher accuracy of predicted cancer risks. The algorithm accurately reclassified IPNs into low or high-risk categories in more than a third of cancerous and benign cases when compared to existing risk assessments.
“These results suggest the potential clinical utility of this deep learning algorithm to revise the probability of cancer among IPNs aiming to decrease invasive procedures and shorten time to diagnosis,” lead author Pierre Massion, MD, Cornelius Vanderbilt Chair in Medicine at Vanderbilt University, told the VUMC Reporter.
Read the study here.
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AI spots potential COVID-19 treatment drug within two days
