In the Race to Build This New Software, Everybody Wins
Prevention & Treatment Early detection is key for treating lung cancer, which is why one lung cancer foundation is challenging tech and healthcare professionals all over the world to build the best new cancer detection software.
Tech, healthcare and open innovation meet to help detect cancer at earlier stages in a new approach to battling the world’s deadliest cancer. Software engineers and data scientists from around the world are working with lung cancer patients and radiologists to collaboratively build software that identifies whether growths of abnormal tissue in the lung are cancerous.
Crowdsourcing a change in healthcare
The Bonnie J. Addario Lung Cancer Foundation (ALCF) is working with DrivenData to run the Lung Cancer Early Detection Challenge: Concept to Clinic. The challenge offers $100,000 in prize money for the collaborative development of open software that changes the way lung cancer is detected. The foundation sees the value that artificial intelligence technology can offer for finding cures for many diseases.
"Building the next iPhone is cool, but it’s not as cool as saving lives..."
Lung cancer is the deadliest cancer, taking more lives than breast, colon and prostate cancer combined. The five-year survival rate for lung cancer is 55 percent when the disease is in the lung, but just four percent once it has spread.
“The earlier lung cancer can be detected, the better,” said Bonnie J. Addario, a 13-year lung cancer survivor and ALCF founder. “This crowdsourcing challenge will create software that cuts down on the number of false positives and detects cancer in its earliest stages when treatment is most successful.”
The coolest job in programming
According to Guneet Walia, Ph.D., senior director of research and medical affairs for ALCF, more than 450 data scientists and engineers are using thousands of lung CT scans to identify patterns and then create software that will accurately identify suspicious nodules. “There are more programmers and data scientists working on this project globally than a tech company could put together. Building the next iPhone is cool, but it’s not as cool as saving lives,” she said.
Throughout this challenge, contributors add features to the software, improve functionality and make algorithms more precise. As these “code patches” are reviewed and adopted, the most advanced version becomes the new starting point.
“Bringing the fields of machine learning and early detection together will take us one step closer to making lung cancer a chronically managed disease,” Addario said.