ReviewAnalytical and bioanalytical chemistry2024
Trends in surface plasmon resonance biosensing: materials, methods, and machine learning.
Review in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
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Who cites it
10 citing papers in PubMed.
- Design of a multilayer photonic crystal biosensor for ocular studies enhanced with machine learning towards the evaluation of proliferative vitreoretinopathy.Scientific reports · 2026Article
- Integration of computational optics and machine learning for optimized SPR-based carcinoembryonic antigen detection.Biomedical optics express · 2026Article
- Review
- Article
- Interpretating SPR-Derived Reaction Kinetics via Self-Organizing Maps for Diagnostic Applications.ACS sensors · 2025Article
- Synthetic Multiepitope Protein-Based Plasmonic Immunosensor for Rapid, Label-Free Detection ofACS infectious diseases · 2025Article
- Article
- Review
- Article
- Analytical and bioanalytical chemistry for digital diagnostics in digital healthcare.Analytical and bioanalytical chemistry · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health.
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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.