|Matthew Dublin is a senior writer at Genome Technology.|
A new application that uses crowdsourcing to diagnose malaria is the latest in a continuing trend of bioinformatics being put into the hands of the masses via online gaming.
A team led by Aydogan Ozcan, an associate professor at UCLA, describes its diagnostic game, called BioGames, in a paper "Distributed Medical Image Analysis and Diagnosis Through Crowd-Sourced Games," which has been accepted for publication in PLoS One.
In the game, players distinguish malaria-infected red blood cells from healthy ones by viewing images obtained from microscopes.
Before the game begins, each player is given a brief online tutorial about what malaria-infected red blood cells look like. After completing training, players are presented with multiple frames of red blood cell images and can use a "syringe" tool to "kill" the infected cells one-by-one and use a "collect-all" tool to designate the remaining cells in the frame as "healthy."
So far, Ozcan's research indicates that a small group of non-experts playing BioGames was collectively able to diagnose malaria-infected red blood cells with an accuracy that was within 1.25 percent of the decisions made by a medical professional.
In the last few years, several online games have been developed to solve scientific problems with data in the form of solutions players have found simply by "winning" the object of the game. These include FoldIt, a game in which players attempt to digitally simulate folding of various proteins and EteRNA that also makes use of crowds to get a better understanding of RNA folding.
The use of crowdsourcing in this context could help overcome limitations in the diagnosis of malaria.
According to Ozcan, "scaling up accurate, automated and remote diagnosis of malaria through a crowd-sourced gaming platform may lead to significant changes for developing countries."