Booz Allen & Kaggle Convene Data Scientists, Medical Community to Improve Cancer Screening using Artificial Intelligence through $1 Million Competition - insideBIGDATA

Competition Aims to Improve Early Detection of Lung Cancer: Low-dose computed tomography (CT) scans can reduce lung cancer deaths by 20 percent, as demonstrated in National Cancer Institute (NCI) sponsored screening trials. This reduction would save more lives each year than any cancer-screening test in history. However, there are significant challenges as low-dose CT scans have a high false-positive rate, creating patient anxiety and potentially leading to costly and unnecessary diagnostic work like invasive biopsies that put patients at risk for collapsed lungs and other complications. Reducing the false positive rate is a critical step in making these scans available to more patients. Participants Will Use Machine Learning and Artificial Intelligence to Scan Lung Images: Using a data set of anonymized high-resolution lung scans provided by the Cancer Imaging Program of the National Cancer Institute, Data Science Bowl participants will develop artificial intelligence algorithms that accurately determine when lesions in the lungs are cancerous, and thereby dramatically decrease the false positive rate of current low-dose CT technology.