FCAI researchers have used AI to model the risk of bacterial infections in surgery. Staphylococcus epidermidis is a bacteria found on the skin of virtually all humans where it lives harmlessly and asymptomatically. However s.epidermidis is also the source of serious infection after surgery. A major question facing scientists wishing to prevent these infections is all members of a s.epidermidis colony are capable of causing an infection, or if some have an increased tendency to do so.
FCAI scientists Johan Pensar and Jukka Corander joined a team of microbiologists and geneticists to unravel this mystery. By combining large-scale population genomics and in vitro measurements of the bacteria, they were able to use machine learning to successfully predict the risk of developing a serious infection from Staphylococcus epidermidis depending on its genetics. This research opens the door for future technology where high-risk genotypes are identified proactively before a patient undergoes surgery, which will reduce the burden of hospital infections caused by S. epidermidis.