4 papers
Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
Yusuf Brima, Marcellin Atemkeng, Lansana Hassim Kallon +4
Childhood anemia affects around 40% of children aged 6-59 months globally and arises from heterogeneous factors, limiting model generalizability. We evaluate a transformer-based ta…
An Empirical Study of Machine Learning Robustness and Scalability for Imbalanced Tabular Clinical Data in Emergency and Critical Care
Yusuf Brima, Marcellin Atemkeng
Every year, millions of patients pass through emergency departments and intensive care units, where clinicians must make high-stakes decisions under time pressure and uncertainty.…
Bridging visual saliency and large language models for explainable deep learning in medical imaging
Paul Valery Nguezet, Elie Tagne Fute, Yusuf Brima +2
The opaque nature of deep learning models remains a significant barrier to their clinical adoption in medical imaging. This paper presents a multimodal explainability framework tha…
A Systematic Review of Low-Rank and Local Low-Rank Matrix Approximation in Big Data Medical Imaging
Sisipho Hamlomo, Marcellin Atemkeng, Yusuf Brima +2
The large volume and complexity of medical imaging datasets are bottlenecks for storage, transmission, and processing. To tackle these challenges, the application of low-rank matri…