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Hospital-Acquired Infections can be Predicted by Machine Learning

by Mohamed Fathima S on December 17, 2018 at 9:54 AM
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Hospital-Acquired Infections can be Predicted by Machine Learning

Machine Learning (ML) used by Finnish researchers predicts the risk of developing a severe and life-threatening infection from 'hospital bug.' This technology will thereby reduce hospital-acquired or nosocomial infections caused by Staphylococcus epidermidis.

Staphylococcus epidermidis is an ubiquitous colonizer of healthy human skin, but it is also a notorious source of serious infections with indwelling devices and surgical procedures such as hip replacements.

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A team of microbiologists and geneticists from the Aalto-University and the University of Helsinki, Finland, combined large-scale population genomics and in vitro measurements of immunologically relevant features of these bacteria.

Using ML, they could successfully predict the risk of developing infection from the genomic features of a bacterial isolate, according to a study published in the journal Nature Communications.
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It has not been known whether all members of the S. epidermidis population colonizing the skin asymptomatically are capable of causing such infections, or if some of them have a heightened tendency to do so when they enter either the bloodstream or a deep tissue.

But, the new finding opens the door for future technology where high-risk genotypes are identified proactively when a person is to undergo a surgical procedure, which has high potential to reduce the burden of nosocomial infections caused by S. epidermidis, the researchers noted.



Source: IANS
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