Researchers at UCLA have created an online crowdsourcing game designed to let players help doctors in key areas of the world speed the lengthy process of distinguishing malaria-infected red blood cells from healthy ones.
For instance, the researchers hope that users of the game can help in areas like sub-Saharan Africa, where malaria accounts for some 20% of all childhood deaths, The disease, which affects about 210 million people annually worldwide, accounts for almost 40% of all hospitalizations throughout Africa.
Typically, malaria is diagnosed by a trained pathologist peering through a conventional light microscope. The time consuming process can overwhelm researchers in countries that have high numbers of cases and limited resources, UCLA researchers said.
The researchers also noted that a significant percentage of cases reported in sub-Sahara Africa are false positives, which lead to unnecessary and costly treatments and hospitalizations.
The crowdsourcing game, which is free to play, works off the assumption that large groups of non-experts can be trained to recognize microscopic images of infectious disease cells with the accuracy of trained pathologists.
So far mostly undergraduate UCLA volunteers have played the game, and have collectively been able to accurately diagnose malaria-infected red blood cells within 1.25% of the accuracy of a pathologist performing the same task, resesarchers said.
"The idea is, if you carefully combine the decisions of people -- even non-experts -- they become very competitive," said Aydogan Ozcan, a UCLA associate professor of electrical engineering and bioengineering and an author of the crowd-sourcing research. "One person's response may be OK, but if you combine 10 to 20, or maybe 50 non-expert gamers together, you improve your accuracy greatly."
The game was created by researchers at the UCLA Henry Samueli School of Engineering and the Applied Science and David Geffen School of Medicine.
While the game currently focuses on diagnosing malaria, the crowdsourcing and gaming-based platform could be adapted for a variety of other biomedical and environmental tasks, the researchers said.
The game can be played on any computer device ranging from cell phones to personal computers, and it can be played by anyone around the world, including children, the researchers said.
By training hundreds, and perhaps thousands, of game players to identify malaria, the UCLA crowdsourcing app could lead to rapid and close to accurate diagnoses at virtually no cost, the researchers said.
"The idea is to use crowds to get collectively better in pathologic analysis of microscopic images, which could be applicable to various telemedicine problems," said Sam Mavandadi, a postdoctoral scholar in Ozcan's research group and the study's first author.
How the game works
Before playing the game, each player is given a brief online tutorial and an explanation of what malaria-infected red blood cells typically look like using sample images.
Then the player goes through a game, in which he or she is shown multiple digital frames of red blood cell images. The player can use a "syringe" tool to "kill" infected cells one-by-one and use a "collect-all" tool to designate the remaining cells in the frame as "healthy."
Within each frame, there are a certain number of cells whose status (i.e., infected or not) is known by the game but not by the players. These control cell images allow Ozcan's team to dynamically estimate the performance of gamers as they go through each frame and also helps the team assign a score for every frame the gamer passes through.
"It could eliminate the current overuse and misuse of anti-malarial drugs, improve management of non-malaria fevers by ruling malaria out, lead to better use of existing funds, and reduce risks due to long-term side-effects of anti-malarial drugs on patients who don't need treatment," said Sam Mavandadi, a postdoctoral scholar in Ozcan's research group and the study's first author.