Most biosensors depend on the characterization of certain analytes namely bacteria, viruses, and proteins amongst other targets which could be achieved by making use of Nano-scale particles micro particles. In these types of biosensors, the particles are given covered with a surface chemistry which makes them stuck to the target analyte which forms clusters as a reaction.
Hence, characterizing and monitoring these particle clusters could tell us whether the target analyte is situated in a sample and by what concentration. The current techniques to undergo such an analysis are very limited and they either depend on bulky and expensive microscopes or are limited in that they can do only a coarse readout which would reduce their applications which address varied needs of the biosensing.
To face these obstacles, the UCLA researchers have created an automated and rapid biosensing technique which is based on holography mixed with deep learning which is currently one of the most successfully used methods when it comes to Artificial Intelligence.