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This research was funded by Laboratorios HIPRA. The funder's role in the design of the study and collection, analysis, interpretation of data, and writing of the manuscript was outlined in the author contributions section (IBR, IBO, RJC, and PM).

Analysis of institutional authors

Garcia-Morante, BeatrizAuthorSibila, MarinaAuthor

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Scoring of swine lung images: a comparison between a computer vision system and human evaluators

Publicated to:Veterinary Research. 56 (1): 9- - 2025-01-13 56(1), DOI: 10.1186/s13567-024-01432-5

Authors: Valeris-Chacin, Robert; Garcia-Morante, Beatriz; Sibila, Marina; Canturri, Albert; Ballara Rodriguez, Isaac; Bernal Orozco, Ignacio; Jorda Casadevall, Ramon; Munoz, Pedro; Pieters, Maria

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Abstract

Cranioventral pulmonary consolidation (CVPC) is a common lesion observed in the lungs of slaughtered pigs, often associated with Mycoplasma (M.) hyopneumoniae infection. There is a need to implement simple, fast, and valid CVPC scoring methods. Therefore, this study aimed to compare CVPC scores provided by a computer vision system (CVS; AI DIAGNOS) from lung images obtained at slaughter, with scores assigned by human evaluators. In addition, intra- and inter-evaluator variability were assessed and compared to intra-CVS variability. A total of 1050 dorsal view images of swine lungs were analyzed. Total lung lesion score, lesion score per lung lobe, and percentage of affected lung area were employed as outcomes for the evaluation. The CVS showed moderate accuracy (62-71%) in discriminating between non-lesioned and lesioned lung lobes in all but the diaphragmatic lobes. A low multiclass classification accuracy at the lung lobe level (24-36%) was observed. A moderate to high inter-evaluator variability was noticed depending on the lung lobe, as shown by the intraclass correlation coefficient (ICC: 0.29-0.6). The intra-evaluator variability was low and similar among the different outcomes and lung lobes, although the observed ICC slightly differed among evaluators. In contrast, the CVS scoring was identical per lobe per image. The results of this study suggest that the CVS AI DIAGNOS could be used as an alternative to the manual scoring of CVPC during slaughter inspections due to its accuracy in binary classification and its perfect consistency in the scoring.

Keywords

<italic>mycoplasma hyopneumoniae</italic>AbattoiAlgorithmArtificial intelligenceArtificial-intelligenceCranioventral pulmonary consolidationLesionsLungMeat inspectionPigPigsPneumoniaPulmonary-lesionsReliabilitySlaughterSlaughterhouse

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Veterinary Research due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 10/167, thus managing to position itself as a Q1 (Primer Cuartil), in the category Veterinary Sciences. Notably, the journal is positioned above the 90th percentile.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-28:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 12.

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 54.

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: http://hdl.handle.net/20.500.12327/3669

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: United States of America.