Artificial Intelligence to Predict the Presence of S. epidermidis

Staphylococcus epidermidis causes nosocomial infections in surgical procedures and indwell devices, which presence can be predicted using machine learning devices.

Ubiquitous colonizer of human skin Staphylococcus epidermidis causes serious nosocomial infections with indwelling devices and surgical procedures like a hip replacement. Now, scientists have found a way to predict the presence of the bacteria with the help of machine learning.//

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.

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‘Artificial Intelligence devices help identify high-risk bacterial infections proactively before a surgical procedure.’

FCAI scientists Johan Pensar and Jukka Corander from the Aalto-University and the University of Helsinki, joined a team of microbiologists and geneticists to unravel this mystery. By combining large-scale population genomics and in vitro measurements of immunologically relevant features of these bacteria, they were able to use machine learning to successfully predict the risk of developing a serious, and possibly life-threatening infection from the genomic features of a bacterial isolate.

This 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.

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Source-Eurekalert

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