Journal of Korean Neurosurgical Society

The Korean Neurosurgical Society (대한신경외과학회)
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Artificial Intelligence-Enhanced Neurocritical Care for Traumatic Brain Injury : Past, Present and Future

  • Kyung Ah Kim (Department of Brain and Cognitive Engineering, Korea University) ;
  • Hakseung Kim (Department of Brain and Cognitive Engineering, Korea University) ;
  • Eun Jin Ha (Department of Critical Care Medicine, Seoul National University Hospital) ;
  • Byung C. Yoon (Department of Radiology, Stanford University School of Medicine, VA Palo Alto Heath Care System) ;
  • Dong-Joo Kim (Department of Brain and Cognitive Engineering, Korea University)
  • Received : 2023.09.06
  • Accepted : 2024.01.04
  • Published : 2024.09.01
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Abstract

In neurointensive care units (NICUs), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of preadmission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU.

Keywords

Acknowledgement

This work was supported by a National Research Foundation of Korea (NRF) Grant funded by the Korean government (Ministry of Science and ICT, MSIT) (No. 2022R1A2C1013205).

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