CrowdDoing machine learning peer to peer randomized RCTs of medicinal foods development architect

CrowdDoing machine learning peer to peer randomized RCTs of medicinal foods app development architect.CrowdDoing is at an early stage of developing an area of emphasis and excellence in medicinal foods and citizen science. Our goal is to be of service to a social innovation device that gathers blood sugar data to develop applications, big data analysis, machine learning, medicinal food alternatives, games where people measure what they eat and collaborate through citizens science, recommendations of health choices for diabetics based on this information, along with distributed peer to peer randomized control trials of medicinal foods. CrowdDoing allows virtual volunteers to help social innovation and social enterprise. More than 1800 volunteers from more than 50 countries have applied