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Bringing machine learning to last mile health challenges Posted on Nov 13 - 2017

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A new microscope will use image recognition software and machine learning technology to identify and count malaria parasites in a blood smear. The EasyScan GO, announced at MEDICA, the medical industry’s leading trade fair, is the result of a partnership between the Global Good Fund, a Seattle-based group funded by philanthropist Bill Gates, and Motic, a China-based company that specializes in manufacturing microscopes. Field tests have demonstrated that the machine learning algorithm is as reliable as an expert microscopist in fighting the spread of drug resistant malaria.

EasyScan GO is the latest example of Global Good’s partnering to bring emerging technologies to health systems in low resource settings. Based at the invention company Intellectual Ventures, Global Good is focused on developing and deploying technologies for the poorest parts of the world. It partners with others to bring the benefits of technological innovation to the hardest markets in the world to reach.

The Global Good motto is “invention saving lives.” But invention means nothing if these products are developed without any consideration of the applicability of that technology in the markets they are meant to serve, said Maurizio Vecchione, senior vice president at Global Good. He emphasized that his team cannot fulfill its mission unless that technology is affordable, appropriate, accessible, and those 3 A’s, as he calls them, are at the center of every Global Good partnership.

Proponents see enormous potential for this technology. Today, machine learning can help tell us we are sick; emerging technologies like artificial intelligence will allow us to prevent illness, according to AnthroTronix founder Corinna Lathan, who wrote a World Economic Forum blog post on ways artificial intelligence and robotics will transform health care.

Several recent partnerships point to how Global Good is working to make sure the benefits of AI, machine learning, and deep learning extend to developing countries.

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