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The acquisition of Antimicrobial Multidrug Resistance (AMR) in patientsadmitted to the Intensive Care Units (ICU) is a major global concern. Thisstudy analyses data in the form of multivariate time series (MTS) from 3476patients recorded at the ICU of University Hospital of Fuenlabrada (Madrid)from 2004 to 2020. 18\% of the patients acquired AMR during their stay in theICU. The goal of this paper is an early prediction of the development of AMR.Towards that end, we leverage the time-series cluster kernel (TCK) to learnsimilarities between MTS. To evaluate the effectiveness of TCK as a kernel, weapplied several dimensionality reduction techniques for visualization andclassification tasks. The experimental results show that TCK allows identifyinga group of patients that acquire the AMR during the first 48 hours of their ICUstay, and it also provides good classification capabilities.

On the Use of Time Series Kernel and Dimensionality Reduction to  Identify the Acquisition of Antimicrobial Multidrug Resistance in the  Intensive Care Unit