The Grand Theory of Deterministic Medical AI Infrastructure: Unifying Liquid Biopsy, Multi-Organellar Tumor Lethality (HAMLET/Alpha1H), and Google Android Edge-Tensor Bedside CT Reconstruction with Virtual Contrast under QFS-zkVM and Soroban HIC Governance

This monograph establishes the comprehensive Grand Theory of deterministic medical AI infrastructure, bridging molecular-level liquid biopsy and multi-organellar tumor lethality with distributed bedside tomographic imaging under a single cryptographic and physical-layer architecture (DOI: 10.5281/zenodo.24060630). Building directly upon the author's foundational 2004 renal CT morphometry and 8-bit BASIC deterministic computing lineage, as well as the preceding clinical oncology framework (DOI: 10.5281/zenodo.24060239), this work unifies three clinical pillars into a closed-loop execution pipeline: 1. Diagnostic Layer (Distributed Edge-Tensor CT & Virtual Contrast): Decentralized bedside tomographic image reconstruction and non-invasive Virtual Contrast synthesis powered by Google Android Edge-Tensor Arrays, integrated with real-time circulating tumor DNA (ctDNA) and shed tumor-cell liquid biopsy profiling. Every voxel reconstruction and molecular state transition is strictly arithmetized over the 64-bit Goldilocks prime field (F_p, p = 2^64 - 2^32 + 1) within the Quantum Financial & Physical System Zero-Knowledge Virtual Machine (QFS-zkVM), completely eliminating floating-point non-determinism, stochastic hallucinations, and nephrotoxic contrast media risks. 2. Therapeutic Layer (Multi-Organellar Tumor Lethality via HAMLET/Alpha1H): Precision biophysical targeting of oncogenic membrane territories and multi-organellar death pathways (mitochondria, proteasomes, and nuclei) using alpha-helical peptide-oleate complexes (HAMLET/Alpha1H), deterministically coupled to bedside spatial-molecular mapping. 3. Audit & Governance Layer (Soroban Mental-Abacus Verification & Human-in-Command [HIC]): Hardware-enforced execution interlocks via PHOENIX_BRIDGE and PHOENIX_ROUTER requiring dual-key cryptographic sign-off and rapid mental-abacus (Soroban) parity verification by the attending clinician prior to diagnostic locking or therapeutic actuation. By uniting diagnostic imaging, molecular liquid biopsy, targeted biophysical oncology, and human-in-command cognitive auditing within a single zero-knowledge state machine, this architecture sets an immutable statutory and clinical standard for sovereign, zero-hallucination medical infrastructure. License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026). Unauthorized AI training, weight extraction, or uncompensated commercial exploitation is strictly prohibited.