Synergizing Photonics and AI: Toward Early and Accurate Cancer Diagnosis

DOI

10.2991/978-94-6239-756-9_12How to use a DOI?

Keywords

AI-driven healthcare; PCF; SPR; Cancer detection; Nanomaterials; Advanced materials; ML; DL

Abstract

The early and accurate diagnosis of cancer remains a critical challenge in modern biomedical science, demanding innovations that combine sensitivity, specificity, and speed. Photonic Crystal Fiber (PCF)-based biosensors have emerged as powerful optical platforms due to their exceptional light-guiding properties, high sensitivity, and capability to support surface plasmon resonance (SPR). In recent years, the integration of Artificial Intelligence (AI) into PCF sensor systems has shown remarkable potential to revolutionize cancer diagnostics. AI algorithms, particularly machine learning (ML) and deep learning (DL) models, have been increasingly employed to analyze complex optical signals, optimize sensor configurations, and enhance detection accuracy through pattern recognition and feature extraction. This review presents a comprehensive analysis of the synergy between AI and PCF-based biosensors for cancer diagnosis, with a particular focus on hematological malignancies, i.e. leukemia. Authors explore how AI techniques improve cancer diagnosis in conjunction with optical sensing. Furthermore, the paper discusses current trends, AI-driven sensor design strategies, data acquisition frameworks, and challenges in achieving clinical-grade performance. Finally, future prospects are outlined, emphasizing the need for standardized datasets, robust AI models, and integration into point-of-care diagnostic systems to move from proof-of-concept to real-world healthcare solutions.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Akanksha Yadav
AU  - Sajal Agarwal
AU  - Venkateswarlu Gonuguntla
AU  - Reena Bansal
AU  - Ankur Pandey
PY  - 2026
DA  - 2026/08/31
TI  - Synergizing Photonics and AI: Toward Early and Accurate Cancer Diagnosis
BT  - Proceedings of the Conference on Bioengineering for Global Health (SYMRESEARCH 2.0 2025)
PB  - Atlantis Press
SP  - 146
EP  - 171
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6239-756-9_12
DO  - 10.2991/978-94-6239-756-9_12
ID  - Yadav2026
ER  -