From Photons to Patients: AI-Driven Photonic Systems for Global Health

Abstract

This paper presents a unifying scientific framework that bridges photonics, artificial intelligence (AI), and biomedical computation to redefine the concept of global healthcare. By translating photon-based information processing into actionable clinical intelligence, the study establishes the foundation of Photon–AI Global Health Systems — an integrative medical architecture where diagnostic, therapeutic, and predictive functions operate with light-speed precision and energy efficiency.

Building upon previous advances in photon-assisted molecular docking, real-time AI–photon interaction mapping, and adaptive therapeutic optimization, this research extends the paradigm from microscopic molecular analysis to macroscopic clinical ecosystems. The proposed model envisions a distributed network of photonic medical processors capable of autonomous decision-making, self-learning diagnostics, and instant therapeutic recalibration across diverse healthcare environments.

Crucially, this approach is designed for global equity: it can function in low-resource regions through miniaturized, solar-powered photonic units, enabling real-time diagnostics and treatment without dependence on large computational infrastructures. By merging quantum photonics, biocomputation, and AI ethics, the system represents a transformative leap toward sustainable, inclusive, and intelligent medicine — where light becomes both the medium and the message of healing.

Keywords: photonics, artificial intelligence, global health, biocomputation, sustainable healthcare, quantum medicine, medical informatics, health equity, photon–AI systems.