Frameworks

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Foundational frameworks

HealthFramework is built on a set of core frameworks designed to bring structure, coherence, and clarity to health data. Together, they form a computational layer that supports individuals, clinicians, and researchers in understanding biological signals in a transparent and responsible way.

This framework organizes laboratory, biometric, and wellness measurements into a structured, harmonized representation. Units, nomenclature, and ranges are standardized, original values are preserved, and ambiguity is reduced through structured confidence metadata.

The goal is to create a stable, reproducible foundation for more advanced physiologic modeling. This layer can support both individual-facing experiences and deeper clinical or research workflows.

The CCE is HealthFramework’s provisional patent-pending system for modeling physiologic drift, and multi-system coherence. Building on the normalization layer, the CCE uses quantitative computations to highlight where physiology is stable, where drift may be emerging, and how these signals accumulate across systems over time.

These insights remain fully explainable and are intended to support clearer conversations— not to assign diagnoses or replace clinical judgment. While demonstrated in MyBiometricsAI™, the CCE can be integrated into clinical, research, or enterprise settings where structured physiologic context is needed.

The RPE surfaces structured constellations of markers that may merit closer attention. These patterns incorporate relationships across biomarkers, physiologic systems, and temporal drift, providing a contextual view that is difficult to obtain from isolated measurements.

Future configuration layers will allow clinicians and researchers to explore emerging or domain-specific patterns in a structured, explainable way, without modifying any underlying computations.

HealthFramework incorporates large language models only within a restricted, educational role. Their purpose is to translate structured outputs into accessible explanations while preserving full visibility of the underlying data.

The reasoning layer is designed to function with different LLMs under strict safety, privacy, and governance constraints. No model is permitted to change core computations or make autonomous decisions; any scientific or structural updates require explicit human review and approval.

Provisional patent-pending work

HealthFramework has filed provisional patent applications covering the deterministic normalization system and the computational coherence frameworks. This establishes a stable foundation for responsible, long-term innovation across clinical, research, and enterprise environments.