M. Atemkeng

FedFarm: Privacy-Preserving Federated Learning for Cassava Disease Diagnosis on Smallholder Farmers' Smartphones

FedFarm demonstrates that privacy-preserving, communication-efficient AI is achievable on the hardware that smallholder farmers already own, offering a replicable blueprint for responsible AI deployment in food-insecure, low-resource agricultural settings across the Global South.

A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data

Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central to managing this burden and increasingly depends on integrating complementary clinical and imaging information. Multimodal deep learning can combine these modalities fo...

Graph Theory, Graph Neural Networks, and Reinforcement Learning in marine ecology: A systematic review of methodologies, theoretical rigour, and future directions

Transformers for 3D medical image analysis: a systematic review of architectural innovations, performance, and clinical applications

This systematic review systematically evaluates 138 peer-reviewed studies published between January 2017 and December 2025 using the PRISMA 2020 framework to reveal a clear dominance of hybrid CNN–Transformer architectures, with MRI representing the most extensively studied modality.