Evidence map›Paper›PMID 41293703›Full record

ArticleBiomedical optics express2025

Deep learning optimized dual-analyte detection-based biosensor for monitoring pregnancy stage using a urine sample.

Kawsar Ahmed, Md Shohidullah, Md Mamun Ali, Francis M Bui, Li Chen, Santosh Kumar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kawsar AhmedDepartment of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK S7N 5A9, Canada.ORCID https://orcid.org/0000-0002-4034-9819
Md ShohidullahHealth Informatics Research Lab, Department of Computer Science and Engineering, Daffodil International University, Birulia, Dhaka-1216, Bangladesh.
Md Mamun AliHealth Informatics Research Lab, Department of Computer Science and Engineering, Daffodil International University, Birulia, Dhaka-1216, Bangladesh.
Francis M BuiDepartment of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK S7N 5A9, Canada.
Li ChenDepartment of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK S7N 5A9, Canada.
Santosh KumarCentre of Excellence for Nanotechnology, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh-522302, India.ORCID https://orcid.org/0000-0003-4149-0096

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a hybrid deep learning (DL) approach for designing and optimizing a photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) multi-analyte biosensor. Using a simulation based on the finite element method (FEM), we generated a comprehensive data set that captures various sensor parameters and refractive index (RI) values. A hybrid recurrent neural network long-short-term memory (RNN-LSTM) model was developed to predict confinement loss (CL), which showed superior performance with an MSE of 0.0014, an MAE of 0.0188, and an R

Identifiers

PMID41293703
PMCPMC12642998

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.