Online crowd-sourcing — in which a task is presented to the public, who respond, for free, with various solutions and suggestions — has been used to evaluate potential consumer products, develop software algorithms and solve vexing research-and-development challenges. But diagnosing infectious diseases?
Working on the assumption that large groups of public non-experts can be trained to recognize infectious diseases with the accuracy of trained pathologists, researchers from the UCLA Henry Samueli School of Engineering and Applied Science and the David Geffen School of Medicine at UCLA have created a crowd-sourced online gaming system in which players distinguish malaria-infected red blood cells from healthy ones by viewing digital images obtained from microscopes.
The UCLA team found that a small group of non-experts playing the game (mostly undergraduate student volunteers) was collectively able to diagnosis malaria-infected red blood cells with an accuracy that was within 1.25 percent of the diagnostic decisions made by a trained medical professional.
The game, which can be accessed on cell phones and personal computers, can be played by anyone around the world, including children.
"The idea is, if you carefully combine the decisions of people — even non-experts — they become very competitive," said Aydogan Ozcan, an associate professor of electrical engineering and bioengineering and the corresponding author of the crowd-sourcing research. "Also, if you just look at one person's response, it may be OK, but that one person will inevitably make some mistakes. But if you combine 10 to 20, maybe 50 non-expert gamers together, you improve your accuracy greatly in terms of analysis."