1 citations · 2 across the 5 of their papers we have counts for
5 papers
Evaluating Fine-Tuned and Base Language Models in Maternal and Vaccination Healthcare for African Settings
Abdulquddus Ajibade, Oluwaseun Odunsi, Iyinoluwa Animasaun +4
Background: Large language models (LLMs) can improve healthcare information delivery in low-resource settings but may produce inaccurate or culturally inappropriate advice. This st…
DobicVLM: Aligning Chest X-Ray Report Generation with Clinically-Grounded Programmatic Rewards via Group Relative Policy Optimization
Thanni Adewuyi, Angelica Obayi, Andem Aniekan +10
Medical imaging is a cornerstone of diagnostics, yet automated chest X-ray report generation struggles with structural adherence, anatomical completeness, and semantic faithfulness…
MamaBench: Benchmarking LLM Robustness in Maternal and Child Health Diagnosis through Counterfactual Clinical Perturbation
Thanni Adewuyi, Anuoluwa Sotome, Samuel Okoko +6
Large language models achieve strong scores on medical benchmarks, yet these benchmarks evaluate each question in isolation, providing no measure of whether a system can distinguis…
Deploying ADVISER: Impact and Lessons from Using Artificial Intelligence for Child Vaccination Uptake in Nigeria
Opadele Kehinde, Ruth Abdul, Bose Afolabi +4
More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring i…
ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeria
Vineet Nair, Kritika Prakash, Michael Wilbur +7
More than 5 million children under five years die from largely preventable or treatable medical conditions every year, with an overwhelmingly large proportion of deaths occurring i…