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Why this conference?

Artificial Intelligence is transforming healthcare, promising great advances in disease detection and treatment. Our understanding of the impact these technologies may have on people, systems and societies is limited, however, especially when it comes to applications in low resource settings. How do we guarantee that AI-assisted technologies don’t perpetuate bias? How do we validate their findings, and assess if they actually improve health outcomes? How do we ensure these technologies are designed by and for local communities? And how do we encourage the development of new sources of data to train machine learning algorithms, especially in data-poor environments?

The inaugural Data Science & AI Summit (DASH) in Africa will inspire, teach and connect innovators in the health data science/AI community within Africa. Through a cross-disciplinary approach that empowers participants to customize the event content, we will explore lessons learned from previous digital health revolutions, highlight new challenges in the advent of AI and cultivate ideas and collaborations that will drive the ecosystem towards scalable impact. READ MORE

 

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Speakers

Multi-disciplinary, international, collaborative: Our speakers come from a wide range of backgrounds, from clinical medicine to entrepreneurship to data science. They work in start-ups, hospitals, community centers, multinational entities, philanthropic organizations and industry.
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Partners


DASH in Africa is a collaboration between the Harvard Global Health Institute, Mbarara University of Science and Technology, the MIT Critical Data Group, and other partners. The project is made possible thanks to the support of the Novartis Foundation.

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Blog

“People have the wrong perception about AI”: Q & A with Richard Kimera

Mbarara University’s Richard Kimera is teaching data science, working on AI for health innovations, and chairing the Innovation Summit for Africa. In this interview, he shares his latest health AI work on detecting cancer re-occurences sooner than currently possible, explains his hope for better recognition of the role research can play in solving Africa’s health problems, and advocates for more collaboration among data scientists and healthcare workers.