Microscopes enhanced with artificial intelligence (AI) may help clinical microbiologists diagnose potentially deadly blood infections and improve patients’ odds of survival.
Researchers from the Beth Israel Deaconess Medical Center (BIDMC) in the US demonstrated that an automated AI-enhanced microscope system is “highly adept” at identifying images of bacteria quickly and accurately.
“This marks the first demonstration of machine learning in the diagnostic area,” said James Kirby from BIDMC.“With further development, we believe this technology could form the basis of a future diagnostic platform that augments the capabilities of clinical laboratories, ultimately speeding the delivery of patient care,” Dr.Kirby said.
According to the study published in the Journal of Clinical Microbiology , the researchers used an automated microscope designed to collect high-resolution image data from microscopic slides. They trained a convolutional neural network (CNN) - a class of artificial intelligence to analyse the visual data and then categorise the bacteria based on their shape and distribution.The machine intelligence sorted the images into three categories of bacteria (rod-shaped, round clusters, and round chains or pairs), with nearly 95 percent accuracy.
Automated classification can “conceivably reduce technologist read time from minutes to seconds,” added Dr.Kirby.
