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UVA Data Points · September 25 · 43 min

The Science Behind Lung Cancer Screening

Lung cancer remains one of the leading causes of cancer death, in part because it is often detected too late. But deciding who should be screened is more complicated than it might seem. In this episode of UVA Data Points, Jeffrey Blume, interim Stephenson Dean of the University of Virginia School of Data Science, and Melinda Aldrich, a cancer epidemiologist at Vanderbilt University, explore how data science is helping researchers better understand lung cancer risk and improve screening decisions. They discuss the role of smoking history, genetics, and environmental exposures; the risks and benefits of screening; and how emerging tools such as AI, medical imaging, biomarkers, and wearable technology could shape the future of early detection. The conversation also examines a fundamental data science challenge: How do you bring together complex and imperfect data to identify the people most likely to benefit from screening, while avoiding unnecessary tests and their potential harms?

0:00 · Introduction: Who Should Be Screened for Lung Cancer?-43:34
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Lung cancer remains one of the leading causes of cancer death, in part because it is often detected too late. But deciding who should be screened is more complicated than it might seem.

In this episode of UVA Data Points, Jeffrey Blume, interim Stephenson Dean of the University of Virginia School of Data Science, and Melinda Aldrich, a cancer epidemiologist at Vanderbilt University, explore how data science is helping researchers better understand lung cancer risk and improve screening decisions. They discuss the role of smoking history, genetics, and environmental exposures; the risks and benefits of screening; and how emerging tools such as AI, medical imaging, biomarkers, and wearable technology could shape the future of early detection.

The conversation also examines a fundamental data science challenge: How do you bring together complex and imperfect data to identify the people most likely to benefit from screening, while avoiding unnecessary tests and their potential harms?

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