Johns Hopkins University has signed a memorandum of understanding with Medopad – digital health leader – to explore new projects using its patient monitoring platform, artificial intelligence and machine learning capabilities. As part of the University’s Global mHealth Initiative and Technology Innovation Center, the two organizations will also develop joint clinical and public health projects and innovations that leverage Medopad’s technology and expertise.
“We look forward to enriching this burgeoning engagement between our two institutions, strengthening this academic-private sector collaboration through rigorous research and clinical innovation to improve lives around the globe,” said Dr. Alain Labrique, Director of the Johns Hopkins University Global mHealth Initiative.
“We’re excited to see what the future holds for public health and technology at Johns Hopkins with Medopad, a global leader in patient engagement. Medopad’s expertise and track record speaks volumes about the potential for even more impactful and valuable innovations for delivering better patient care,” added Dr. Paul Nagy, Deputy Director, Johns Hopkins Medicine Technology Innovation Center.
With this collaboration Medopad and Johns Hopkins University aim to:
Medopad’s technologies and access to sophisticated Artificial Intelligence engines, advanced analytics and large existing data sets will allow machine learning algorithms to become increasingly robust particularly as large, varied data sets of risk factors and outcomes are introduced.
Dan Vahdat, co-founder and CEO at Medopad comments: “We are delighted to work alongside Johns Hopkins - a prestigious, globally renowned institution. By combining our resources and expertise we will be able to create innovative mobile health solutions and improve patient care on a global scale.”
Through this MoU, Johns Hopkins University, through its Global mHealth Initiative and Technology Innovation Center networks, will embark on preparing an adaptable framework of process, outcome and econometric indicators within a Monitoring and Evaluation framework that could enable Medopad and its users to evaluate the impact of innovations on processes and outcomes. Based on an ‘adaptive learning system’ model, the framework will allow users to track process, output and outcome measures as a program is deployed and grows.
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