Game on! UCLA researchers use online crowd-sourcing to diagnose malaria
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 team found that a small group of non-experts playing the game 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 idea is that if you carefully combine the decisions of people — even of non-experts — the results become very competitive. If you just look at one person's response, it may be correct, 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.