Awards

Seth Adu-Afarwuah of the University of Ghana in Ghana and Julie Croff of Oklahoma State University Center for Health Sciences in the U.S. will assess the effects of nutritional supplementation on adolescent brain development in low-resource settings to support interventions. Nutritional behavior majorly impacts the rapid stage of adolescent neurodevelopment, which in turn impacts future generations through effects on maternal and paternal nutritional status, cognition and parenting. However, little is known about typical adolescent neurodevelopment in low- and middle-income countries, where 90% of the world’s adolescents live. They will recruit 40–60 post-pubertal adolescents in Accra, Ghana, measure their corticolimbic system development over nine months, and assess their problem-solving, planning and cognitive functioning. In another cohort of 40–60 post-pubertal adolescents, they will measure adherence to an eight-month twice-daily micronutrient supplementation program and associated nutritional outcomes.

Nana Kofi Quakyi of the Aurum Institute in Ghana will develop an AI-powered decision support tool for antibiotic prescribers to improve appropriate antimicrobial usage and combat antimicrobial resistance (AMR) in Ghana. AMR is a major public health concern, with the highest mortality rates occurring in Africa. To address this, Ghana's National Action Plan for Antimicrobial Use and Resistance (2018) identified the need for support tools that provide personalized, adaptable, and context-sensitive recommendations. They will develop an interactive, AI-powered clinical decision support tool that allows prescribers to enter prompts, respond to system queries, and receive personalized, real-time antibiotic prescribing recommendations, such as drug, dosage, and duration of administration. The model will be trained with a comprehensive dataset consisting of clinical guidelines, research data, expert opinions, and surveillance evidence that has been reviewed for its representativeness. The proposal includes field testing, iterative refinement, and engagement with stakeholders to ensure effectiveness and scalability.

Darlington Akogo of MinoHealth AI Labs in Ghana will leverage a multimodal Large Language Model (LLM) to generate accurate and comprehensive medical reports based on the analysis of medical images to reduce the need for manual reports and enhance diagnostic capabilities for radiologists and clinicians. African healthcare systems have excessively high patient-to-doctor ratios and prevalent diseases and severely inadequate numbers of radiologists. They will fine-tune a multimodal LLM applied to radiology and medical imaging using a supervised approach with a labeled dataset of medical images and corresponding reports collected from facilities across Ghana and Africa. The platform will enable interactive conversations with clinicians seeking answers to specific queries or clarifications regarding medical images. They will use metrics and humans to evaluate the model and assess its ability to generate accurate and comprehensive medical reports. They will also conduct field testing with clinicians and individuals from diverse demographics.

Floris Sonnemans of Degas Ghana Limited in Ghana will apply AI technology to support African smallholder farmers to implement more climate-adaptive and regenerative agricultural (RA) techniques, such as crop diversification, and scale climate action across the continent. Africa only contributes 3.8% of global greenhouse gas emissions but experiences the harshest impacts, particularly on food production. However, protective RA techniques are relatively new and challenging to adopt, and there are not enough field agents to support farmers and respond to queries. To address this, they will integrate a Large Language Model (LLM)-based system trained on RA manuals into their existing agent-facing application. This system will provide an easy interface for farmers to access information and guidance to effectively implement RA practices, such as biochar application, minimal tillage, and permanent organic soil coverage. The application will be field tested amongst field agents and farmers.