## 2 Literature Review
### Features  
According to the literature, the features derived from heart rate are most valuable when predicting LOS [11; 12; 13; 14]. This is, however, because heart rate is regulated by the autonomic nervous system and is highly influenced by immunologic and cardiovascular changes. Research in both adults and preterm infants indicates that low heart rate variability is often succeeded by a sepsis episode and occurs often before obvious clinical signs are recognized [26]. This abnormal pattern in heart rate serves as a potential marker or indicator of impending sepsis in these infants. The study suggests that monitoring heart rate characteristics could potentially aid in the early identification of sepsis, allowing for prompt intervention and treatment. Moreover, it has been shown that preterm infants present an overall transient deceleration in heart rate hours leading up to the diagnosis of sepsis [26]. Other variables such as blood pressure, temperature, respiratory rate, and oxygen saturation are considered to be less valuable when predicting sepsis. According to [PERSON] et al. (2015) [14], this is due to several reasons. First, blood pressure is monitored by arterial catheters only at the beginning of the NICU stay and often not at the time during which the infant can develop sepsis. Second, temperature is not a trustful measure as \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & **LogR** & **NB** & **DT** & **RandF** & **KNN** & **SVM** & **ADA** & **GB** \\ \hline [PERSON] et al. & & & & X & & X & & X & \\ (2020) [8] & & & & X & & X & & & \\ [PERSON] et al. & & X & & & & & & & \\ (2020) [17] & & & & & & & & & \\ [PERSON] et al. & & X & & & & X & & & \\ (2021) [7] & & & & & & & & & \\ [PERSON] et al. * & & X & & X & & X & & X & X & X \\ (2019) [9] & & & & & & & & & \\ \hline \hline \end{tabular}  
* this work assessed EOS instead of LOS[PERSON]  
\end{table} 
Table 1: Overview of all ML models that have been assessed by recent literature. incubators automatically adjust environmental temperature to keep the infants temperate within normal range. Third, respiratory rate is often confounded by inaccuracy of the chest impedance signal. Lastly, acute changes in oxygen saturation have not yet been thoroughly studied for their association with sepsis. While the impact of acute changes in oxygen saturation on sepsis is an area of interest, it has not yet been extensively investigated. Oxygen saturation levels can fluctuate rapidly during critical illness, including sepsis. However, the specific relationship between acute changes in oxygen saturation and the presence or progression of sepsis remains largely unexplored. Further research is needed to elucidate this association and understand the potential role of oxygen saturation as a clinical marker or predictor of sepsis, as studies have shown that an increased heart rate deceleration increased respiratory instability [17]. Furthermore, a study by [PERSON] et al. (2017) [3] showed that a cross-correlation index between heart rate and oxygen saturation (SpO2) proved to be the best illness predictor for the preclinical detection of sepsis. Next, [PERSON] et al. (2015) [14] indicated that heart rate is strongly modulated by respiration and blood pressure changes. This is in line with the study of [PERSON] et al. (2021) [7], who found both respiration and heart rate variability features to be of the importance when predicting LOS using [PERSON]. Lastly, the perfusion index (PFI) (i.e., the ratio of the pulsatile blood flow to the non-pulsatile static blood flow) is considered a useful parameter when predicting late onset sepsis [27]. Thus, although these features are less convincing according to the literature compared with HRV features, we considered them to be promising and included them in this study. Interestingly, to the best of our knowledge, no literature is available yet of the use of PFI and SpO2 as predictors of LOS in preterm infants in a machine learning context.