Future Directions: Multimodality Monitoring and Machine Learning

In this chapter, the evolution of neurocritical care is traced from historical perspectives to its current status as a globally recognized medical specialty. The focus is on multimodal monitoring in the neurological intensive care unit (neuroICU) and machine learning (ML). The integration of various monitoring techniques such as intracranial pressure (ICP), cerebral autoregulation (CAR), brain tissue oxygenation (PbtO2), and cerebral microdialysis (CMD) is explored. The emergence of non-invasive methods for ICP monitoring is discussed, offering potential advantages, particularly in resource-limited settings. While these techniques provide extensive data, the chapter emphasizes the challenges of interpreting and analyzing such information. In that context, ML presents itself as a promising solution to process the overwhelming amount of data generated by multimodal monitoring, highlighting its potential in predicting outcomes, identifying patient phenotypes, and enhancing overall patient care in the field of neurocritical care and neurotraumatology.