Have You Played MOLT?

Can you really gamify the business of diagnosing infectious diseases? That’s what Ozcan Research Group at UCLA is hoping. Each year, half a billion people are infected with malaria and almost three million people die as a result. In the most severe cases of the disease, fatality rates can exceed 20%.

The stated goal of Ozcan is to “create photonics based telemedicine technologies toward next generation smart global health systems.” What does that mean? It means that the team has developed MOLT – a game for anyone to play, in which they look at pictures of healthy and malaria infected cells and try to achieve a high score by accurately identifying those cells that are infected. The crowd’s accuracy will, in turn, help develop new technologies that will aid in diagnoses.

The game is pretty simple. You create a profile, log on and are taken through a five-step tutorial on how to recognize malaria and which buttons to press in order to identify those cells. By the end of the twenty or so slide deck, you are given a score based on how accurate your diagnoses were. Even I (with no medical training and not the most sophisticated pattern recognition skills on the planet) achieved accurate diagnoses 85% of the time. However, most of the time, non-professional gamers report with anaccuracy within 1.25% of trained professionals.

The hope is that this game will help in developing a self-learning image analysis and diagnostics framework that will help in the diagnosis of malaria in those areas that are most at risk for malarial infection in the developing world.

What do you think of the untrained crowd helping in the diagnosis of infectious disease? How else is crowdsourcing serving the developing world?

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