Enhancing Community Health with New AI Resources – GAIN
Ghana AI Research Network (GAIN) shared a post on LinkedIn:
“When we first released the Twi–English maternal health Q/A dataset, the goal was simple: make health information more accessible for the communities that need it most. The response in this short period made it clear that the work shouldn’t stop there. So we decided to make the rest openly accessible.
Today, we’re releasing the next set of multilingual maternal-health datasets for Ghana — each one built to support real-world applications, community health work, and AI systems that actually understand how people speak.
Every dataset contains 20,000 Q/A pairs, covering topics from pregnancy to postpartum care: danger signs, ANC visits, nutrition, newborn care, medications, family planning, and more.
Here’s the collection:
English-only (20,000 pairs)
Twi–English (20,000 code-mixed pairs)
Ewe–English (20,000 code-mixed pairs)
Hausa–English (20,000 code-mixed pairs)
Ga–English (20,000 code-mixed pairs)
This work is part of GAIN’s commitment to build AI resources rooted in Ghana’s languages, culture, and health realities. Use them for research, model training, mobile apps, chatbots, or whatever you’re building next.
The important thing is impact.
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Advancing AI, Empowering Society.
Henry Nunoo-Mensah, Francisca Adoma Acheampong, Emmanuel Awuni Kolog, Justice Kwame Appati, Delali Kwasi Dake, Alidu Abubakari, Florence Ofori, Anthony Addae, Benjamin Asubam Weyori, Eric Tutu Tchao, KNUST Department of Computer Engineering”
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