October 26, 2020
This marks the first demonstration of machine
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.The machine
intelligence learned how to sort the images into the three categories of
bacteria (rod-shaped, round clusters, and round chains or pairs), ultimately
achieving nearly 95 percent accuracy.Next, they trained a convolutional neural
network (CNN) - a class of artificial intelligence modelled on the mammalian
visual cortex and used to analyse visual data - to categorise bacteria based on
their shape and distribution.These characteristics were selected to represent
bacteria that most often cause bloodstream infections, the rod-shaped bacteria
including E coli, the round clusters of Staphylococcus species, and the pairs or
chains of Streptococcus species.In this case, blood samples taken from patients
with suspected bloodstream infections were incubated to increase bacterial
numbers.
This marks the first demonstration of machine learning in the
diagnostic area," said James Kirby from BIDMC. bacteria, artificial
intelligence.The automated system could help alleviate the current lack of
highly trained microbiologists.Automated classification can ameliorate the
shortage of human technologists by helping them work more efficiently,
"conceivably reducing technologist read time from minutes to seconds," Kirby
said.The automated system could help alleviate the current lack of highly
trained microbiologists, expected to worsen as 20 per cent of technologists
reach retirement age in the next five years.To train the AI system, the
scientists fed their unschooled neural network more than 25,000 images from
blood samples prepared during routine clinical workups.By cropping these images
- in which the bacteria had already been identified by human clinical
microbiologists - the researchers generated more than 100,000 training images.
(Representational image) Microscopes enhanced with artificial intelligence (AI)
may help clinical microbiologists diagnose potentially deadly blood infections
and improve patients odds of survival, according to a study. Then, slides were
prepared by placing a drop of blood on a glass slide and stained with dye to
make the bacterial cell structures more visible.According to the study published
in the Threaded
Rod Astm Suppliers Journal of Clinical Microbiology, the researchers used an
automated microscope designed to collect high-resolution image data from
microscopic slides."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," Kirby
said. 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
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