SUMMARY
# Biomechanical Impact Profiles and Chronic Traumatic Encephalopathy Phenotype Heterogeneity
## Background and Rationale
# Biomechanical Impact Profiles and Chronic Traumatic Encephalopathy Phenotype Heterogeneity: A Computational Systems Approach
Traumatic brain injury (TBI) represents a significant public health burden affecting millions globally, with long-term sequelae including chronic traumatic encephalopathy (CTE), a progressive neurodegenerative disease characterized by pathological tau
METHODOLOGY NOTES
**Phase 1: Data Collection and Preprocessing (Weeks 1-4)**
• Collect biomechanical impact data from 500+ documented TBI cases across multiple sports and military cohorts
• Gather CTE neuropathological assessments including tau protein distribution, neuroinflammation markers, and brain atrophy patterns
• Compile clinical phenotype data including cognitive assessments (MMSE, MoCA), behavioral evaluations (NPI), and functional outcomes (GOS-E)
• Standardize impact metrics: peak linear acceleration (g-force), rotational velocity (rad/s), impact duration, and cumulative exposure indices
• Perform quality control and missing data imputation using multiple imputation methods
**Phase 2: Biomechanical Profile Classification (Weeks 5-8)**
• Apply unsupervised machine learning algorithms (K-means clustering, hierarchical clustering) to identify distinct impact profile clusters
• Validate clustering using silhouette analysis and gap statistic (target ≥3 distinct clusters)
• Characterize each clus