Introduction: Traumatic brain injury (TBI) remains a leading cause of long-term disability with an estimated direct medical cost exceeding 20 million a year and societal costs surpassing 50 billion a year. Our team at Corewell Health has been modeling pediatric TBI using acute omics and aims to transition into adult modeling with both pediatric/adult long-term sequelae discovery. To achieve this, we require guidance on acute-to-chronic transitions informed by perspectives of patients, caregivers, and clinical experts. Methods: We developed Baymax (Behavioral and ArtificiallY-Modeled Analysis eXchange), a hybrid AI framework to model acute-to-chronic transitions. Using GPT-4o, Baymax simulated 100 journeys spanning pre-admission, acute intervention, and up to 5-year follow-up for pediatric or adult TBI. Each journey seeds key clinical anchors into clinician forums, guideline repositories, and literature, while capturing patient, caregiver, and clinician voices via Reddit, Facebook, HealthUnlocked, Inspire, BrainLine. org, and YouTube. Logical pathflows integrate these components into coherent, human-centered narratives linking the patient, caregiver, and clinician in shared experiences. Results: Pediatric cases had a higher rate of full recovery (40%) compared to adults (15%), with pediatric cases having more severe TBI (21% vs 6%). The pediatric cohort had more cases (35%) with persistent symptoms than adults (15%). However, adults had 60% of cases with longer sequelae (memory impairment, fatigue, language/speech, executive dysfunction, emotional dysregulation, identity crisis, balance/coordination, cognitive slowing, self-harm/isolation risk). Both cohorts had a shared cluster with moderate TBI and language disruption benefiting from cognitive behavioral therapy. Pediatric patients had more caregiver support, while adult cases often involved isolation, shame, identity loss, and grief. Conclusions: Simulated journeys of TBI interventions for patients and clinicians suggest an urgent need for adult social support post-TBI. Further generations of journeys guided by diversity and socioeconomic factors may provide additional insights. Hospital systems can benefit by linking their EHR, omic datasets, and outcomes with approaches like Baymax, optimizing satisfaction and outcomes.
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