Introduction:

Traumatic brain injury (TBI) and HIV-associated neurocognitive impairment (NCI) are the leading causes of long-term disability, with effects on cognitive, motor, and psychological functioning. Even with improved acute care and antiretroviral therapy, successful and individualized neurorehabilitation is a continuing need. New technologies, specifically artificial intelligence (AI), virtual reality (VR), and telerehabilitation platforms, present new potential to enhance outcomes through individualized interventions and decision-making in real-time.

Methodology:

This review synthesizes evidence from recent clinical trials, AI model performance analysis, and neurorehabilitation trials for TBI as well as HIV-related NCI. The AI algorithms developed for TBI were compared on the basis of diagnostic accuracy, prognostic models, and rehabilitation optimization. The computational neurorehabilitation paradigms were evaluated for their capacity to merge the digital flow of data among patients, clinicians, and predictive systems. Cognitive rehabilitation devices, such as immersive games and distant training systems, were assessed regarding accessibility, customization, and compliance in HIV-impacted populations.

Results:

AI models exhibited up to 95.6% accuracy in mortality and functional outcome prediction in TBI. AI-enhanced neuroimaging enhanced diagnostic sensitivity. Non-invasive brain stimulation, VR, robot-assisted therapy, and computer-based training were partially effective in TBI rehabilitation. Technology-enabled cognitive rehabilitation enhanced adherence and motivation in HIV-related NCI, especially with gamified and immersive settings. Yet disparities in digital access and the absence of large-scale trials were observed.

Conclusion:

AI and computational neurorehabilitation have important potential to propel individualized therapy in TBI and HIV-related NCI. Satisfying ethical issues, interoperability of data, and availability will be crucial for their broader clinical deployment. Future research should emphasize solid, large-scale trials to prove and extend these technology-based interventions.