Portable system for the prediction of anemia based on the ocular conjunctiva using Artificial Intelligence
This work addresses the need for a fast, cost-effective, and non-invasive anemia screening method, particularly for young children in resource-limited settings, though it appears incremental as it builds on existing concepts of using conjunctival pallor for detection.
The researchers tackled the problem of non-invasive anemia screening by developing a portable system that uses smartphone photos of the ocular conjunctiva and AI techniques, achieving promising initial results for detecting conjunctival pallor anemia in Peruvian young children.
Anemia is a major health burden worldwide. Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and a blood test. In this work we propose a non-invasive, fast, and cost-effective screening test for iron-deficiency anemia in Peruvian young children. Our initial results show promising evidence for detecting conjunctival pallor anemia and Artificial Intelligence techniques with photos taken with a popular smartphone.