Journal of Lasers in Medical Sciences

Abstract

Introduction: This review examines the question, “Can artificial intelligence enhance the antimicrobial effectiveness of photodynamic therapy (PDT)?” We discuss current knowledge and uncertainties surrounding this topic, address the limitations of existing approaches—such as the complexities of predicting reactive oxygen species generation and the necessity for large datasets for AI training—and propose future strategies that integrate AI with PDT.

Methods: In the present literature review, the authors used keywords such as Antimicrobial photodynamic therapy, Photosensitizers, and Artificial intelligence, and conducted a literature search via Google Scholar and PubMed from January 2000 to November 2024.

Results: The reviewed literature indicates that AI has been used to enhance antimicrobial therapy by identifying optimal photosensitizers, predicting treatment outcomes, and enabling real-time monitoring. In antimicrobial PDT (aPDT), AI facilitates personalized therapy by selecting appropriate agents and light parameters based on microbial profiles, although clinical implementation remains limited.

Conclusion: While the combination of AI and PDT is theoretically possible, it has not yet been implemented. Consequently, this article may serve as a foundation for future research on personalizing laser-based treatments through AI.