collaborators

4 papers

cs.AI2026

From Manuals to Maintenance: Fine-Tuning MedGemma for Multi-Modal Imaging System Support in Low-Resource Settings

Bernes Lorier Atabonfack, Zion Kongbi Nfo, Ahmed Tahiru Issah +9

Imaging device downtime is a major barrier to healthcare delivery in low- and middle-income countries (LMICs), often driven by limited access to specialized biomedical engineering…

cs.CV2026

On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation

Idaya Seidu, Ahmed Tahiru Issah, Charles B. Delahunt +1

Malaria remains a leading cause of mortality in resource-limited settings, where expert microscopists are scarce. Automated diagnosis based on microscopy images thus has strong pot…

cs.CV2026

SGMCE: Segment-Grounded Morphological Concept Explanation for Malaria Parasite Species Identification in Thick Blood Smears

Ahmed Tahiru Issah, Charles B. Delahunt, Carine Mukamakuza

Malaria diagnosis in endemic regions depends on species-level identification of Plasmodium parasites in thick blood smears, but deep learning detectors classify detections without…

cs.AI2026

Empowering Medical Equipment Sustainability in Low-Resource Settings: An AI-Powered Diagnostic and Support Platform for Biomedical Technicians

Bernes Lorier Atabonfack, Ahmed Tahiru Issah, Mohammed Hardi Abdul Baaki +5

In low- and middle-income countries (LMICs), a significant proportion of medical diagnostic equipment remains underutilized or non-functional due to a lack of timely maintenance, l…