Temporal Progression: A case study in Porcine Survivability through Hemostatic Nanoparticles
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Date
2021-05-26
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Abstract
This paper focuses on the analysis of time series
representation of blood loss and cytokines in animals
experiencing trauma to understand the temporal progression
of factors affecting survivability of the animal. Trauma related
grave injuries cause exsanguination and lead to death. 50% of
deaths especially in the armed forces are due to trauma
injuries. Restricting blood loss usually requires the presence of
first responders, which is not feasible in certain cases.
Hemostatic nanoparticles have been developed to tackle these
kinds of situations to help achieve efficient blood coagulation.
Hemostatic nanoparticles were administered into trauma
induced porcine animals (pigs) to observe impact on the
cytokine and blood loss experienced by them. In this paper we
present temporal models to study the impact of the hemostatic
nanoparticles and provide snapshots about the trend in
cytokines and blood loss in the porcine data to study their
progression over time. We utilized Piecewise Aggregate
Approximation, Similarity based Merging and clustering to
evaluate the impact of the different hemostatic nanoparticles
administered. In some cases the fluctuations in the cytokines
may be too small. So in addition we highlight situations where
temporal modelling that produces a smoothed time series may
not be useful as it may remove out the noise and miss the
overall fluctuations resulting from the nanoparticles. Our
results indicate certain nanop