Structural Medicine v1.6: Predictive Structural Dynamics and Time-dependent Collapse in Lifespan Systems

This work presents Structural Medicine v1.6, an extension of the Integrated Structural Generation (IGS) framework toward predictive modeling of disease progression using time-dependent structural dynamics. The central contribution is the introduction of a time-dependent structural decay rate, λ(t), which enables biological and cognitive systems to be described not as deterministic trajectories but as stochastic structural processes. Unlike conventional models that assume constant decay rates, this framework demonstrates that structural degradation fluctuates over time and exhibits transient excursions toward instability. Using longitudinal ADNI data, we empirically validate that: Structural decay is inherently time-dependent and non-uniform. The variance of λ(t) increases systematically with disease progression. Instability emerges as intermittent threshold crossings before irreversible collapse. Sustained instability onset provides a structural criterion for transition into irreversible regimes. The framework integrates: Individual-level dynamics (Fig19: λ(t) fluctuations) Population-level structure (Fig20: distribution of λ(t)) Predictive instability detection (Fig21: threshold-based sustained onset) Together, these results establish a unified, minimal, and directly testable structural approach to understanding disease progression as a stochastic and predictive dynamical system. This work provides a foundation for: Early detection of structural instability in neurodegenerative diseases Predictive modeling of individual disease trajectories A unified structural interpretation of emergence, persistence, and collapse in lifespan systems The ADNI dataset is not redistributed and must be obtained separately.