<p>Scientists have developed an app that allows people to easily screen for pancreatic cancer and other diseases by just clicking a selfie.<br /><br />One of the earliest symptoms of pancreatic cancer, as well as other diseases, is jaundice, a yellow discolouration of the skin and eyes caused by a buildup of bilirubin in the blood, researchers said.<br /><br />The ability to detect signs of jaundice when bilirubin levels are minimally elevated - but before they are visible to the naked eye - could enable an entirely new screening programme for individuals at risk, they said.<br /><br />The BiliScreen app, developed by researchers at the University of Washington in the US, uses a smartphone camera, computer vision algorithms and machine learning tools to detect increased bilirubin levels in a person's sclera, or the white part of the eye.</p>.<p><br />The team developed a computer vision system to automatically and effectively isolate the white parts of the eye, which is a valuable tool for medical diagnostics.<br /><br />The app then calculates the colour information from the sclera-based on the wavelengths of light that are being reflected and absorbed—and correlates it with bilirubin levels using machine learning algorithms.<br /><br />To account for different lighting conditions, the team tested BiliScreen with two different accessories: paper glasses printed with coloured squares to help calibrate colour and a three dimensional (3D) printed box that blocks out ambient lighting.<br /><br />"Pancreatic cancer is a terrible disease with no effective screening right now," said Jim Taylor, professor at University of Washington.<br /><br />"Our goal is to have more people who are unfortunate enough to get pancreatic cancer to be fortunate enough to catch it in time to have surgery that gives them a better chance of survival," Taylor added.<br /><br />In an initial clinical study of 70 people, the BiliScreen app-used in conjunction with a 3D printed box that controls the eye's exposure to light-correctly identified cases of concern 89.7 per cent of the time, compared to the blood test currently used.</p>
<p>Scientists have developed an app that allows people to easily screen for pancreatic cancer and other diseases by just clicking a selfie.<br /><br />One of the earliest symptoms of pancreatic cancer, as well as other diseases, is jaundice, a yellow discolouration of the skin and eyes caused by a buildup of bilirubin in the blood, researchers said.<br /><br />The ability to detect signs of jaundice when bilirubin levels are minimally elevated - but before they are visible to the naked eye - could enable an entirely new screening programme for individuals at risk, they said.<br /><br />The BiliScreen app, developed by researchers at the University of Washington in the US, uses a smartphone camera, computer vision algorithms and machine learning tools to detect increased bilirubin levels in a person's sclera, or the white part of the eye.</p>.<p><br />The team developed a computer vision system to automatically and effectively isolate the white parts of the eye, which is a valuable tool for medical diagnostics.<br /><br />The app then calculates the colour information from the sclera-based on the wavelengths of light that are being reflected and absorbed—and correlates it with bilirubin levels using machine learning algorithms.<br /><br />To account for different lighting conditions, the team tested BiliScreen with two different accessories: paper glasses printed with coloured squares to help calibrate colour and a three dimensional (3D) printed box that blocks out ambient lighting.<br /><br />"Pancreatic cancer is a terrible disease with no effective screening right now," said Jim Taylor, professor at University of Washington.<br /><br />"Our goal is to have more people who are unfortunate enough to get pancreatic cancer to be fortunate enough to catch it in time to have surgery that gives them a better chance of survival," Taylor added.<br /><br />In an initial clinical study of 70 people, the BiliScreen app-used in conjunction with a 3D printed box that controls the eye's exposure to light-correctly identified cases of concern 89.7 per cent of the time, compared to the blood test currently used.</p>