Besim Bilalli
Papers
1
Total Citations
26
H-Index
1
About
Besim Bilalli is a leading researcher at the intersection of artificial intelligence, biomedical engineering, and global health diagnostics. His primary research areas include automated medical imaging, machine learning for disease detection, and low-cost diagnostic technologies for resource-limited settings. Bilalli’s most notable contribution is the development of **iMAGING**, a novel automated system for malaria diagnosis that integrates artificial intelligence tools with a universal, low-cost robotized microscope. This groundbreaking work, published in 2023 and already garnering 26 citations, addresses the critical challenge of malaria diagnosis in sub-Saharan Africa, where 247 million cases were reported in 2021. By replacing the need for expert microscopists with AI-driven analysis, iMAGING has the potential to dramatically improve diagnostic accuracy and accessibility in underserved regions. Bilalli’s research exemplifies how engineering innovation can directly combat global health crises, and his work continues to inspire new approaches to automated disease surveillance and point-of-care diagnostics.
Research Focus
Key Achievements
Top Papers
- 1