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Crowdsourcing Game Helps Diagnose Infectious Diseases

Posted by Soulskill on 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."

4 of 25 comments (clear)

  1. applying machine learning? by tomlue · · Score: 5, Interesting

    Whenever I see these games I wonder if there is some effort to solve the task with ml as well. It seems like if you are getting a large number of players then you should have data on how those players are classifying the red blood cells. Given that data we can at least attempt a couple different techniques at a classifier.

    The benefit could be two fold. On one hand a decent classifier could 'help eliminate the high cost and sometimes poor accuracy of diagnosis.' On the other hand if a diagnostician is looking at a blood sample having a classifier give some probability of classification (ie. saying 'this sample is 90% probable to be malaria infected') could help the doctor in their diagnosis.

    I'd love to work on that problem. A very quick search of google scholar and citeseer doesn't pop up anything on the subject though, and I don't see any api on the linked site.

    1. Re:applying machine learning? by fuzzyfuzzyfungus · · Score: 5, Insightful

      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.

    2. Re:applying machine learning? by chooks · · Score: 4, Insightful

      From the referenced PDF:

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

      --
      -- The Genesis project? What's that?
  2. Re:Didn't know a DDX could have the word balls in by Anonymous Coward · · Score: 4, Funny

    Once the troll population reaches sufficent levels:

    "I have a sore throat and a slight fever."
    *evaluating*
    *You have AIDS, leprosy, and lupus.*