AI-Based Decision Support System for Traumatic Brain Injury: A Survey

Area of Science:

• Neuroscience
• Medical Informatics
• Biomedical Engineering

Background:

• Traumatic brain injury (TBI) is a leading global cause of death and disability.
• Effective TBI management necessitates rapid clinical assessment and decision-making.
• Computer-aided systems are crucial for analyzing complex TBI data.

Purpose of the Study:

• To review recent progress in artificial intelligence (AI)-based decision support systems for TBI.
• To cover AI applications in TBI diagnosis, severity assessment, and prognosis.
• To highlight challenges in developing AI for TBI.

Main Methods:

• Literature review of AI applications in TBI.
• Analysis of current research on AI-driven TBI decision support.
• Identification of challenges related to data heterogeneity and quality.

Main Results:

• AI shows promise in improving TBI diagnosis and severity assessment.
• AI tools can aid in predicting long-term TBI complications.
• Development faces hurdles due to data variability and noise.

Conclusions:

• AI-based decision support systems hold significant potential for TBI care.
• Further research is needed to overcome data challenges and enhance AI reliability.
• AI integration can improve patient outcomes in traumatic brain injury cases.