ETHIOPIA – The Ethiopian Public Health Institute (EPHI) and benshi.ai have announced a three-year Memorandum of Understanding (MOU)with benshi.ai to improve public health research outcomes in Ethiopia through the use of artificial intelligence (AI) and machine learning.

The focus areas under this MOU include AI capacity building for EPHI researchers, using AI tools to generate research, and promoting AI adoption by publicizing the outcomes of our collaboration.

Benshi.ai will begin by delivering a one-week introductory AI and machine learning course to EPHI management, over 50 researchers, and frontline health workers in Ethiopia.

The collaboration will also deploy artificial intelligence tools to generate research and evidence on specific public health nutrition issues.

Additionally, as the MOU has stipulated that it will make the collaboration’s findings public in order to promote the use of AI to conduct high-quality nutrition research in Ethiopia.

EPHI’s Food Science and Nutrition Research Directorate is leading this collaboration with benshi.ai. As a result, one of the primary areas of study will be dietary challenges and malnutrition.

This collaboration marks the first time AI has been used in public health nutrition research at the national level in Ethiopia.

EPHI aims to leverage advanced technologies and techniques to provide data-driven insights and boost strategies and outcomes for public health in Ethiopia by collaborating with benshi.ai, a non-profit funded by the Bill & Melinda Gates Foundation.

The Ethiopian Public Health Institute, a research arm of the Ministry of Health (MOH), was established to improve the health of the Ethiopian general public through research on priority health and nutrition issues for evidence-based information utilization and technology transfer; effective public health emergency management; the establishment of a quality laboratory system; and the training of public health researchers and practitioners for best public health interventions.

Malnutrition is a significant public health issue in many developing countries. It is one of the most serious health issues affecting Ethiopian women and children.

In Sub-Saharan Africa (SSA), the country has the second highest rate of malnutrition. The common forms of malnutrition in Ethiopia include acute and chronic malnutrition, iron deficiency anemia (IDA), vitamin A deficiency (VAD), and iodine deficiency disorder (IDD).

Micronutrient deficiencies remain a problem in Ethiopia, and it has adverse health impacts on children, pregnant mothers, and men according to a USAID report on the country’s nutrition profile.

Director of EPHI’s Food Science and Nutrition Research Directorate, Dr. Masresha Tesema, said: “Machine learning is key to excellent research. EPHI’s collaboration with benshi.ai has a lot of promise for integrating AI and machine learning in nutrition research.”

“Machine learning and artificial intelligence can help nutritionists conduct high-quality research. Researchers will be able to embrace and sustain machine learning methodologies while delivering high-quality research output as a result of our collaboration.” Dr Tesema added.

The partnership will be in force from 2022 through 2024.

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