Evidence map›Paper›PMID 40520424›Full record

ArticleFrontiers in veterinary science2025

Evaluating the efficacy of bioelectrical impedance analysis using machine learning models for the classification of goats exposed to Haemonchosis.

Aftab Siddique, Phaneendra Batchu, Arshad Shaik, Priyanka Gurrapu, Tharun Tej Erukulla, Cornileus Ellington, Andrea L Rubio Villa, Davia Brown, Ajit Mahapatra, Sudhanshu Panda and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Bioelectrical Impedance Analysis as a Non-Invasive Approach to EstimateAnimals : an open access journal from MDPI · 2025
    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

15 authors.

Aftab SiddiqueDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Phaneendra BatchuDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Arshad ShaikDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Priyanka GurrapuDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Tharun Tej ErukullaDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Cornileus EllingtonDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Andrea L Rubio VillaDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Davia BrownDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Ajit MahapatraDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.
Sudhanshu PandaInstitute for Environmental Spatial Analysis, University of North Georgia, Oakwood, GA, United States.
Eric MorganInstitute for Global Food Security, Queen's University, Belfast, United Kingdom.
Jan Van WykDepartment of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa.
David Shapiro-IlanUnited States Department of Agriculture- Agriculture Research Services, Fruit and Tree Nut Research, Byron, GA, United States.
Govind KannanDepartment of Poultry Sciences, Auburn University, Auburn, AL, United States.
Thomas H TerrillDepartment of Agricultural Sciences, Fort Valley State University, State University Drive, Fort Valley, GA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid identification and assessment of animal health are critical for livestock productivity, especially for small ruminants like goats, which are highly susceptible to blood-feeding gastrointestinal nematodes, such as

Indexed as

bioelectrical impedancegastrointestinal parasitesHaemonchus contortusmachine learningveterinary diagnostics

Identifiers

PMID40520424
PMCPMC12162282

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.