Evidence map›Paper›PMID 40872683›Full record

ArticleVeterinary sciences2025

A Non-Invasive Diagnostic Platform for Canine Leishmaniasis Using VOC Analysis and Distributed Veterinary Infrastructure.

Marius Iulian Mihailescu, Violeta Elena Simion, Alexandra Ursachi, Varanya Somaudon, Aylen Lisset Jaimes-Mogollón, Cristhian Manuel Durán Acevedo, Carlos Cuastumal, Laura-Madalina Lixandru, Xavier Llauradó, Nezha El Bari and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Veterinary sciences, 2025. 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. Review
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

17 authors.

Marius Iulian MihailescuFaculty of Engineering and Computer Science, SPIRU HARET University, 47 Fabricii Street, 076144 Bucharest, Romania.ORCID 0000-0001-9655-9666
Violeta Elena SimionFaculty of Veterinary Medicine, SPIRU HARET University, 256 Basarabia Boulevard, Sector 3, 030045 Bucharest, Romania.ORCID 0000-0001-6034-601X
Alexandra UrsachiFaculty of Veterinary Medicine, SPIRU HARET University, 256 Basarabia Boulevard, Sector 3, 030045 Bucharest, Romania.
Varanya SomaudonMUI-ROBOTICS, Moo 1, Rattanathibet Rd., Saima, Nonthaburi 11000, Thailand.
Aylen Lisset Jaimes-MogollónFaculty of Engineering and Architecture, University of Pamplona, Pamplona 543050, Colombia.
Cristhian Manuel Durán AcevedoFaculty of Engineering and Architecture, University of Pamplona, Pamplona 543050, Colombia.ORCID 0000-0002-5241-2950
Carlos CuastumalFaculty of Engineering and Architecture, University of Pamplona, Pamplona 543050, Colombia.ORCID 0000-0001-8996-5666
Laura-Madalina LixandruInstitute of Veterinary Medicine and Animal Sciences, Estonian University of Life Sciences, Kreutzwaldi 62, 51014 Tartu, Estonia.
Xavier LlauradóR&D Digital Health Department, NVISION, 08028 Barcelona, Spain.
Nezha El BariBiosensors and Nanotechnology Group, Faculty of Sciences, Moulay Ismaïl University, Zitoune, Meknes B.P. 11201, Morocco.
Benachir BouchikhiBiosensors and Nanotechnology Group, Faculty of Sciences, Moulay Ismaïl University, Zitoune, Meknes B.P. 11201, Morocco.ORCID 0000-0002-9403-0846
Dhafer LaouiniLaboratoire de Micriobiologie Moléculaire, Vaccinologie et Biotechnologie Appliquée/LR16IPT01, Institut Pasteur de Tunis, Université Tunis Elmanar, Tunis 1068, Tunisia.
Mohamed Fethi DiouaniLaboratoire de Micriobiologie Moléculaire, Vaccinologie et Biotechnologie Appliquée/LR16IPT01, Institut Pasteur de Tunis, Université Tunis Elmanar, Tunis 1068, Tunisia.
Adam Borhan Eddine BessouChadli Bendjedid University, El-Taref, BP N° 73, EL Tarf 36000, Algeria.ORCID 0009-0001-8931-2435
Nazim MessaoudiChadli Bendjedid University, El-Taref, BP N° 73, EL Tarf 36000, Algeria.ORCID 0009-0007-6560-8657
Fayçal ZeroualChadli Bendjedid University, El-Taref, BP N° 73, EL Tarf 36000, Algeria.ORCID 0000-0003-3332-5701
Valentina MarascuFaculty of Engineering and Computer Science, SPIRU HARET University, 47 Fabricii Street, 076144 Bucharest, Romania.ORCID 0000-0002-5170-1398

Funding

European Union's Horizon 2020 Research and Innovation Staff Exchange (RISE) programme under the Marie Skłodowska-Curie 101007653
6 · The paper itself

Abstract

This article describes a new software architecture for the non-invasive detection of canine leishmaniasis disease. The proposed platform combines gas-sensing technologies, artificial intelligence (AI), and modular cloud-based software components to identify disease-specific volatile organic compounds (VOCs) found in dog breath and hair samples. The system, which has a multi-tier architecture that includes data collection, pre-processing, machine learning-based analysis, diagnosis-request processing, and user interfaces for veterinarians, faculty researchers, and dog owners, has been integrated into a Li-ion Power website plug-in. The primary goal of implementing the proposed platform is to detect parasites at any point they are infectious to a host. This includes detecting parasites at all stages of their life cycle, where they can infect a new host. In addition, this is crucial for accurate diagnosis, effective treatment, and preventing further transmission.

Indexed as

artificial intelligence in animal healthcanine leishmaniasiscloud-based architecturemachine learningnon-invasive testingveterinary diagnosticsvolatile organic compounds (VOCs)

Identifiers

PMID40872683
PMCPMC12390277

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.