ArticleBiosensors2021
A Fiber-Optic Surface Plasmon Resonance Sensor for Bio-Detection in Visible to Near-Infrared Images.
Article in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Electrochemical detection of cardiovascular diseases and treatment platform based on microfluidic technology.Mikrochimica acta · 2025Review
- [Corneal endothelial cell photography: comparison of smartphones].Die Ophthalmologie · 2023Article
- A Synergistic Dual-Channel Sensor for Ultrasensitive Detection ofBiosensors · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In this paper, we demonstrate a fiber-optic surface plasmon resonance (FO-SPR) biosensor based on image processing and back propagation (BP) neural network. The transmitted light of the FO-SPR sensor was captured by using visible (VIS) and near-infrared (NIR) CMOS sensors. The optical information related to the SPR effect was extracted from images based on grayscale conversion and an edge detection algorithm. To achieve accurate monitoring of refractive index (RI) changes, the grayscale means of the VIS and NIR images and the RGB summation of the edge-detected images were used as training and test inputs for the BP neural network. We verified the effectiveness and superiority of this sensing system by experiments on sodium chloride solution identification and protein binding detection. This work is promising for practical applications in standardized biochemical sensing.
Indexed as
Identifiers
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.