ReviewJournal of advanced research2026
Evanescent wave-based optical biosensors for innovations, medical application and future perspectives.
Review in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- U-shaped fiber-optic biosensor with gold nanoparticle-assisted signal amplification for allergy-related biomarker detection.Analytical and bioanalytical chemistry · 2026Article
- Surface and Interface Engineering in Integrated Photonic Sensors: Performance Trade-Offs, Stability, and Benchmarking.Micromachines · 2026Review
- Extreme sensitivity label-free biosensing platform based on topologically disruptive phase nano-optics.Microsystems & nanoengineering · 2026Article
- Engineered Protein Modification: A New Paradigm for Enhancing Biosensing Sensitivity and Diagnostic Accuracy.Biosensors · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEvanescent wave (EW)-based optical biosensors have rapidly evolved into indispensable tools for real-time, non-invasive, and ultra-sensitive detection of biomolecular interactions. By enabling label-free analysis with unprecedented precision, they have significantly reshaped the landscape of clinical diagnostics and personalized medicine. In recent years, interdisciplinary innovations spanning materials science, nanotechnology, photonic integration, and microfluidics have propelled EW biosensors beyond their conventional roles, endowing them with capabilities that were once considered unattainable. AIM OF REVIEW: This review aims to provide a comprehensive and up-to-date synthesis of recent advances in EW-based biosensing technologies, with a particular emphasis on their transformative applications in the medical field. Specifically, it seeks to critically evaluate the progress achieved across major biosensor platforms and to explore how these innovations are bridging the gap between fundamental research and clinical translation. KEY SCIENTIFIC CONCEPTS OF REVIEW: The review systematically examines three representative EW biosensor platforms-surface plasmon resonance (SPR) sensors, silicon photonic sensors, and optical fiber sensors-highlighting their operating principles and recent breakthroughs. Innovations such as nanomaterial-enhanced sensitivity, chip-scale multiplexing, and portable point-of-care designs are pushing the boundaries of biosensing performance. Furthermore, emerging approaches, including seamless microfluidic integration and artificial intelligence-driven data interpretation, are recognized as essential for developing next-generation intelligent and autonomous biosensors. These advances collectively position EW biosensors to revolutionize precision diagnostics and enable real-time health monitoring, heralding a new era of biomedical science.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.