Abstract
The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving
the way for significant strides in patient diagnosis, treatment, and prognostication
in neurocritical care. These technologies offer the potential to unravel complex patterns
within vast datasets ranging from vast clinical data and EEG (electroencephalogram)
readings to advanced cerebral imaging facilitating a more nuanced understanding of
patient conditions. Despite their promise, the implementation of AI and ML faces substantial
hurdles. Historical biases within training data, the challenge of interpreting multifaceted
data streams, and the “black box” nature of ML algorithms present barriers to widespread
clinical adoption. Moreover, ethical considerations around data privacy and the need
for transparent, explainable models remain paramount to ensure trust and efficacy
in clinical decision-making.
This article reflects on the emergence of AI and ML as integral tools in neurocritical
care, discussing their roles from the perspective of both their scientific promise
and the associated challenges. We underscore the importance of extensive validation
in diverse clinical settings to ensure the generalizability of ML models, particularly
considering their potential to inform critical medical decisions such as withdrawal
of life-sustaining therapies. Advancement in computational capabilities is essential
for implementing ML in clinical settings, allowing for real-time analysis and decision
support at the point of care. As AI and ML are poised to become commonplace in clinical
practice, it is incumbent upon health care professionals to understand and oversee
these technologies, ensuring they adhere to the highest safety standards and contribute
to the realization of personalized medicine. This engagement will be pivotal in integrating
AI and ML into patient care, optimizing outcomes in neurocritical care through informed
and data-driven decision-making.
Keywords
machine learning - artificial intelligence - neurocritical care - precision medicine
