ArticleBiomedical optics express2026
Integration of computational optics and machine learning for optimized SPR-based carcinoembryonic antigen detection.
Article in Biomedical optics express, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Artificial intelligence enabled performance evaluation of an enhanced SPR biosensor for malaria diagnosis.Scientific reports · 2026Article
- Hybrid machine learning driven optimization of multilayer SPR sensor for high sensitivity milk fat detection.PloS one · 2026Article
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
No grant is acknowledged in the PubMed record.
Abstract
Carcinoembryonic antigen (CEA) is an effective biomarker for diagnosing and tracking cases of liver cancer, breast cancer, and colorectal cancer. In this study, a hybrid SPR biosensor combined with black phosphorus and MgO/Cu/MgO multi-layer is designed and developed to fully utilize the capabilities of black phosphorus in confining electric fields and increasing sensor sensitivity. The brute force algorithm is utilized to optimize sensor parameters. The accuracy of artificial neural network and adaptive neuro-fuzzy inference system models in simulating sensor responses is thoroughly validated. The designed biosensor has a sensitivity of 409.02 deg/RIU, a figure of merit of 132.25, and a quality factor of 146.65 RIU
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.