Scientists have developed a novel smartphone-based technique to diagnose viral infections that uses a deep-learning algorithm to identify viruses in metal nanoparticle-labelled samples.
The system correctly identified clinically relevant concentrations of Zika, hepatitis B, or hepatitis C in 134 patient samples with 98.97% sensitivity.
Mobile phone subscribers are increasing worldwide – including in sub-Saharan African populations that are heavily burdened by infection outbreaks.
To harness smartphones’ virus-detecting potential, Mohamed Draz and colleagues developed a process in which samples are loaded onto microchips and labelled with platinum nanoprobes, after which a hydrogen peroxide solution is added to the chip, reacting with the platinum-nanoprobe complex to form bubbles. This bubble signal is detected using a smartphone with a trained deep-learning algorithm that determines the viral content.
