Technology once again takes a quantum leap. Who would have thought selfies could help save lives? A smartphone app, called ‘BiliScreen,’ can now help identify the early signs of pancreatic cancer with a selfie.

Here’s How Biliscreen works:

A team of researchers at the University of Washington who previously developed an app, called BiliCam, that detected Jaundice in newborns by taking pictures of their skin have now developed a similar app for adults that detects Jaundice even before it is visible to the naked eye-with a quick selfie.



“The eyes are a really interesting gateway into the body — tears can tell you how much glucose you have, sclera can tell you how much bilirubin is in your blood,” said senior author Shwetak Patel, the Washington Research Foundation Entrepreneurship Endowed Professor in Computer Science & Engineering and Electrical Engineering.  “Our question was: Could we capture some of these changes that might lead to earlier detection with a selfie?”



Source: University of Washington


Jaundice, a yellow discoloration of the skin and eyes caused by a buildup of bilirubin in the blood, is one of the earliest symptoms of pancreatic cancer. The reason for the occurrence of Jaundice in case of Pancreatic cancer is due to cancerous growth at the head of the pancreas that causes the narrowing of the bile duct, leading to a buildup of bilirubin in the blood. Bilirubin is a substance produced from the breakdown of old red blood cells in the liver. The app can detect even the slightest elevated level of bilirubin by analyzing the whites of the person’s eyes (sclera) and correlating the results with bilirubin levels when taking a selfie.


The BiliScreen app helps identify bilirubin levels in the blood by analyzing the color information from the sclera- based on the wavelengths of light that are being absorbed and reflected.


As per the experts, the most lethal aspect of Pancreatic cancer is that when the tumor is most treatable, there are usually no symptoms that can help them identify the disease. “Pancreatic cancer is a terrible disease with no effective screening right now,” said  Jim Taylor, a researcher on the project. “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.”

Designed with the help of machine learning tools and computer vision algorithms, BiliScreen when tested, was around 90 percent as accurate as a blood test in identifying the levels of bilirubin in an initial study of 70 people.




The app uses the smartphone’s built-in camera along with the two accessories to reduce the effects of external lighting: paper glasses printed with colored squares to help calibrate color and a 3-D printed box that blocks out ambient lighting.


The accessories: (1) 3D-printed box that controls the eyes’ exposure to light and (2) paper glasses with colored squares for calibration



The app can also take the burden of frequent bilirubin monitoring off the patients’ shoulders by allowing them to test it in the privacy of their homes as per needed. It is also far more convenient and cheaper than a blood test which otherwise is the only other way for confirming some cancers. “In the privacy of their own homes ― some might catch the disease early enough to undergo treatment that could save their lives,” said Mariakakis.

The research team further intends to make this app available to a wider range of people who are suffering from jaundice and other conditions along with improving the app by eliminating the need to use accessories with it.

The development of apps like these that implement and automate the ways that doctors use their learning to detect symptoms more accurately, precisely, and consistently is one of the best applications of technology today. As the chief science officer at the Pancreatic Cancer Action Network, Lynn Matrisian, said, “Although there are many hurdles to validating the clinical usefulness and practicality of this approach, we are delighted to see advanced technology applied to pancreatic cancer early detection where there is such dire need.”