An AI-integrated spatial auxiliary decision-support model for historic and cultural blocks based on the spatial triad.

Abstract

The findings of this study offer valuable insights for the development of targeted rehabilitation strategies. Understanding the specific cognitive and behavioural patterns identified can help clinicians tailor interventions that address underlying mechanisms rather than only symptoms. For example, integrating adaptive training programs that focus on enhancing self-regulation and social cognition may improve patient outcomes. Furthermore, the demonstrated role of contextual and individual difference factors suggests that rehabilitation plans should be personalised, taking into account demographic and psychosocial variables to maximise efficacy. Incorporating technology-assisted approaches, such as virtual reality or AI-driven feedback systems, could further enhance engagement and facilitate real-time monitoring of progress. Overall, these implications highlight the need for a holistic, flexible, and patient-centred rehabilitation framework to promote sustainable recovery.