Aroa Silgado

Universitat Autònoma de Barcelona

Papers

1

Total Citations

3

H-Index

1

About

Aroa Silgado is a researcher at the forefront of applying artificial intelligence and low-cost automation to global health diagnostics, with a primary focus on infectious diseases like malaria. Her most cited work, published in 2024, evaluates an AI-based diagnostic tool paired with a universal, low-cost robotized microscope for the automated detection of malaria. This study directly addresses a critical bottleneck in global health: the reliance on expert microscopists for the gold-standard diagnosis of Plasmodium parasites, a process prone to human error and limited in resource-poor settings. By demonstrating that automated image analysis can rival traditional microscopy, Silgado’s research paves the way for scalable, accurate, and accessible diagnostic solutions. With 3 citations already, this work is gaining traction as a practical innovation for field deployment. Her contributions lie at the intersection of biomedical engineering and tropical medicine, aiming to democratize expert-level diagnostics. For students and researchers, Silgado’s work exemplifies how AI and frugal engineering can transform public health, offering a compelling model for tackling diagnostic disparities in endemic regions.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Evaluation of an Artificial Intelligence-Based Tool and a Universal Low-Cost Robotized Microscope for the Automated Diagnosis of Malaria
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Universitat Autònoma de Barcelona

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago