A low blood pressure (hypotension, as mean arterial pressure < 65 mmHg) in patients on the intensive care unit (ICU) is associated with adverse outcomes and death. Proactive treatment with the use of a predictive alarm could improve patient outcome. The Hypotension Prediction Index (HPI) is a machinelearning algorithm that uses arterial blood pressure waveforms to calculate the probability of impending hypotension. Prior to clinical implementation, the HPI model needs to be validated. In previously published validation protocols of the HPI, possible sources of bias were identified. Therefore, the primary objectives were to assess HPI performance on the ICU population by using a clinically relevant validation protocol and to evaluate the differences between previous protocols. Secondary objectives included evaluation of subgroup performance and the effect of individual validation protocol settings on the subsequent results. The three applied validation protocols used conceptually different methods to classify predictions (e.g. as a true or false alarm). The primary forward sliding window (FSW) protocol labels each single prediction based on hypotension occurrence thereafter. The forward tumbling window (FTW) groups predictions in nonoverlapping time windows to only classify the window based on hypotension occurrence thereafter. The backward (BW) protocol labels the onsets of hypotension based on alarm occurrence at ’t’ minutes prior to onset, hence ’backward’ in time. Identical metrics were used to quantify performance. For secondary analyses the FSW protocol was used. Performance for the FSW protocol was reduced compared to the FTW and BW protocol. Using the FDAapproved alarm settings for FSW, FTW and BW (t=10min) protocols, sensitivity was 0.59, 1.00 and 0.83, respectively. Positive predictive values were 0.41. 0.83 and 1.00, respectively. For the FSW protocol the median [IQR] timetohypotension was 3.3 [1.0 to 7.3] min, for an alarm defined as the last of consecutive alarms prior to hypotension. Reducing the minimal mean arterial pressure in the definition of nonhypotension from 75 to 65 mmHg reduced the area under the precision recall curve from 0.82 to 0.31. Omission of a washout period of 30 min increased the positive predictive value from 0.41 to 0.64. This thesis demonstrates the importance of validation methodology and the generalizability of the Hypotension Prediction Index to the intensive care unit population. The definition of nonhypotension and a washout period strongly influenced the results. Overall, the results demonstrate the ability of the HPI to predict hemodynamic instability in ICU patients. Therefore, validation results support the introduction of the HPI to the ICU for clinical use. However, the optimal alarm threshold and clinical benefit remain to be evaluated in future clinical studies.