Catch up on stories from the past week (and beyond) at the Slashdot story archive


Forgot your password?
For the out-of-band Slashdot experience (mostly headlines), follow us on Twitter, or Facebook. ×
Biotech Medicine Games Science

Crowdsourcing Game Helps Diagnose Infectious Diseases 25 25

Posted by Soulskill
from the grand-theft-antibody dept.
Lucas123 writes "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. So far, those playing the game have collectively been able to accurately diagnose malaria-infected blood cells within 1.25% of the accuracy of a pathologist performing the same task (PDF). The researchers hope that users of the game can help eliminate the high cost and sometimes poor accuracy of diagnosis in areas like sub-Saharan Africa, where malaria accounts for some 20% of all childhood deaths."
This discussion has been archived. No new comments can be posted.

Crowdsourcing Game Helps Diagnose Infectious Diseases

Comments Filter:
  • by fuzzyfuzzyfungus (1223518) on Friday May 04, 2012 @10:50AM (#39890371) Journal
    I suspect that you could dodge some of the liability issues in this case.

    Yeah, if Joe American goes in to MGH for a CT, pays north of 5k(after insurance), and learns that some unfeeling robot, rather than a tired radiologist, misdiagnosed him, it'll be malpractice lawyer time.

    However, in areas where the current standard of care often doesn't include pathologist inspection of cells; because there aren't any qualified pathologists, or they are too expensive for the majority of patients, I suspect you'll find a much greater willingness to embrace the idea that you can perform the diagnosis with a glorified webcam(wasn't there some story on slashdot a little while back about some research group hacking microscope optics onto cellphone cameras?) and a nickel worth of CPU time...

    It sounds crass when you say it in so many words; but what you can get away with in medicine is very much a product of what the alternative would be. If the current standard is sufficiently dire, even mediocrity counts as lifesaving. If it just so happens that machines are actually really good at this classification problem, all the better.
  • by chooks (71012) on Friday May 04, 2012 @11:44AM (#39891065)

    From the referenced PDF:

    we also developed an automated machine learning algorithm to detect the presence of malaria parasites,

The perversity of nature is nowhere better demonstrated by the fact that, when exposed to the same atmosphere, bread becomes hard while crackers become soft.