Evidence map›Paper›PMID 41971621›Full record

ArticleFrontiers in artificial intelligence2026

Portable electrochemical impedance biosensing with DRT-enabled machine learning for detecting

Yang Tian, Ziyu Liu, Chaitanya Pallerla, Siavash Mahmoudi, Ramesh Bahadur Bist, Yiting Xiao, Terry Howell, Jeyamkondan Subbiah, Dongyi Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Yang TianDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.
Ziyu LiuDepartment of Animal Science, University of Arkansas, Fayetteville, AR, United States.
Chaitanya PallerlaDepartment of Food Science, University of Arkansas, Fayetteville, AR, United States.
Siavash MahmoudiDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.
Ramesh Bahadur BistDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.
Yiting XiaoDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.
Terry HowellDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.
Jeyamkondan SubbiahDepartment of Food Science, University of Arkansas, Fayetteville, AR, United States.
Dongyi WangDepartment of Biological and Agriculture Engineering, University of Arkansas, Fayetteville, AR, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ensuring food safety requires rapid and accurate detection of pathogens such as

Indexed as

distribution of relaxation timeelectrochemical biosensorelectrochemical impedance spectroscopyEscherichia coli O157:H7field-deployable sensormachine learningpartial least squaresportable detection

Identifiers

PMID41971621
PMCPMC13064606

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.