Dialogues of delivery: a multilingual question answer dataset for maternal healthcare in East African languages
| dc.contributor.author | Kimera,Richard | |
| dc.contributor.author | Kuyeso, Rogers | |
| dc.contributor.author | Maleka,Emmanuel | |
| dc.contributor.author | Tukamushaba,Fortunate | |
| dc.contributor.author | William,Wasswa | |
| dc.contributor.author | Mwavu,Rogers | |
| dc.contributor.author | Bamutura,David Sabiiti | |
| dc.contributor.author | Ngonzi, Joseph | |
| dc.contributor.author | Ainomugisha, Brenda | |
| dc.contributor.author | Namuli,Alexer | |
| dc.contributor.author | Namiiro,Proscovia | |
| dc.contributor.author | Nyakato, Clare | |
| dc.contributor.author | Celi,Leo Anthony | |
| dc.contributor.author | Kaggwa,Fred | |
| dc.date.accessioned | 2026-08-21T09:12:20Z | |
| dc.date.issued | 2026-06-02 | |
| dc.description.abstract | Objective There is a critical scarcity of domain-specific, clinically grounded Natural Language Processing (NLP) resources for African languages. In Western Uganda, linguistic diversity creates a barrier to maternal healthcare, as mothers lack access to health information in their native languages. The objective of this dataset is to provide a high quality, in-language medical corpus to enable the development and fine-tuning of Large Language Models (LLMs) and conversational AI tools for maternal health in resource-constrained settings. Data description The “Dialogues of Delivery” dataset is a multilingual, parallel corpus comprising 3,694 question and-answer pairs presented in four languages: English, Luganda, Runyankore, and Swahili (14,800 total entries). Using facility-based convenience sampling at two health facilities in Western Uganda, primary data was collected via structured, open-ended questionnaires from 150 participants (expectant/postpartum mothers and maternal healthcare providers). The dataset underwent a rigorous forward-backward translation protocol by certified linguists and human-in-the-loop clinical validation by independent medical professionals. The dataset captures core maternal health domains, providing a culturally and clinically validated foundation for Afrocentric AI development | |
| dc.description.sponsorship | Science for Africa (SFA) Foundation through the Grand Challenges Africa program under Grant Reference Number SFA-R15-145. | |
| dc.identifier.citation | Kimera, R., Kuyeso, R., Maleka, E., Tukamushaba, F., William, W., Mwavu, R., ... & Kaggwa, F. (2026). Dialogues of delivery: a multilingual question-answer dataset for maternal healthcare in East African languages. BMC Research Notes. | |
| dc.identifier.uri | https://ir.must.ac.ug/handle/123456789/4439 | |
| dc.language.iso | en_US | |
| dc.publisher | BMC Research Notes | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Maternal health | |
| dc.subject | Multilingual health communication | |
| dc.subject | Clinical dialogue dataset | |
| dc.subject | Large Language Models | |
| dc.subject | Conversational artificial intelligence | |
| dc.subject | Low-resource settings | |
| dc.title | Dialogues of delivery: a multilingual question answer dataset for maternal healthcare in East African languages | |
| dc.type | Article |
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