From Photons to Patients: AI-Driven Photonic Systems for Global Health
| dc.contributor.author | Barack Ndenga | |
| dc.date.accessioned | 2025-11-02T10:52:36Z | |
| dc.date.issued | 2025-10-29 | |
| dc.description | This publication presents a unifying framework connecting photonic computation, artificial intelligence, and biomedicine toward equitable, energy-efficient healthcare. By translating photon-based information processing into clinical decision support, the study establishes the foundation of Photon–AI Global Health Systems — a networked approach where diagnostic, therapeutic, and predictive medical functions operate at light speed. The model integrates previous advances in photon–AI interaction mapping, real-time molecular monitoring, and therapeutic optimization (articles 19–30), extending them into large-scale medical infrastructures capable of functioning autonomously and sustainably in diverse global contexts, including resource-limited regions. This work demonstrates how light, as a carrier of both information and energy, can be leveraged to decentralize medical intelligence, reduce computational energy consumption, and enhance health equity worldwide. It establishes AI-driven photonic medicine as both a scientific and ethical frontier, redefining global health as a balance between information, energy, and life itself. | |
| dc.description.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. | |
| dc.description.sponsorship | None | |
| dc.identifier.uri | https://repository.africarxiv.org/handle/1/10510 | |
| dc.identifier.uri | https://doi.org/10.60763/africarxiv/10250 | |
| dc.language.iso | en | |
| dc.publisher | Publisher | |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | |
| dc.title | From Photons to Patients: AI-Driven Photonic Systems for Global Health | |
| dc.type | Article |
