  The presence of bacteria or fungi in the bloodstream of patients is abnormal
and can lead to life-threatening conditions. A computational model based on a
bidirectional long short-term memory artificial neural network, is explored to
assist doctors in the intensive care unit to predict whether examination of
blood cultures of patients will return positive. As input it uses nine
monitored clinical parameters, presented as time series data, collected from
2177 ICU admissions at the Ghent University Hospital. Our main goal is to
determine if general machine learning methods and more specific, temporal
models, can be used to create an early detection system. This preliminary
research obtains an area of 71.95% under the precision recall curve, proving
the potential of temporal neural networks in this context.
