Computerworld - 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.
With the promise of big data (solving the unsolvable problems, informing better decision making, creating new products and services, discovering patterns and acting on them, etc.) on the horizon, what has really changed? Does this mean that everything we know and do with not-so-big data should be tossed?
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