Abstract
X-rays and other forms of medical imaging let doctors peer into the body, revealing the internal structure of organs and tissues without invasive surgery. Doctors use the results to identify abnormalities such as broken bones, diagnose diseases such as cancer, or even monitor the health of a foetus within the womb. Although this technology is remarkable, the images aren’t useful in isolation. Experts must analyse the resulting data and parse what is healthy or unhealthy from the noise. Yiqiao Yin, Jaiden Schraut, Leon Liu and Jonathan Gong have created new machine learning technologies to support that crucial interpretation, focusing on X-rays and lung health.
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