ArticleVeterinary research2020
Scoring pleurisy in slaughtered pigs using convolutional neural networks.
Article in Veterinary research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed, 29 citations in OpenAlex.
- Development of a urogenital scoring system and evaluation of macroscopic parameters influencing the sexual cycle in slaughtered sows.Porcine health management · 2025Article
- Non-Invasive Human-Free Diagnosis Methods for Assessing Pig Welfare at Abattoirs: A Systematic Review.Animals : an open access journal from MDPI · 2025Review
- Welfare of beef cattle.EFSA journal. European Food Safety Authority · 2025Article
- Detecting ear lesions in slaughtered pigs through open-source convolutional neural networks.Porcine health management · 2025Article
- Scoring of swine lung images: a comparison between a computer vision system and human evaluators.Veterinary research · 2025Article
- Cross-species AI: shifting a convolutional neural network from pigs to lambs to detect pneumonia at slaughter.Frontiers in veterinary science · 2025Article
- Impact of porcine respiratory disease complex on carcass weight and meatiness: quantitative insights from a mixed-model analysis.BMC veterinary research · 2024Article
- Scoring Enzootic Pneumonia-like Lesions in Slaughtered Pigs: Traditional vs. Artificial-Intelligence-Based Methods.Pathogens (Basel, Switzerland) · 2023Article
- Opportunities for Regulatory Authorities to Assess Animal-Based Measures at the Slaughterhouse Using Sensor Technology and Artificial Intelligence: A Review.Animals : an open access journal from MDPI · 2023Review
- Welfare of calves.EFSA journal. European Food Safety Authority · 2023Article
- Review on the methodology to assess respiratory tract lesions in pigs and their production impact.Veterinary research · 2023Review
- Comparative Efficacy in Challenge Dose Models of a Toxin Expressing Whole-Cell Vaccine against Eight Serovars ofAnimals : an open access journal from MDPI · 2022Article
- Meat safety legislation and its opportunities and hurdles for innovative approaches: A review.Food control · 2022Review
- Welfare of pigs on farm.EFSA journal. European Food Safety Authority · 2022Article
- Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs.Animals : an open access journal from MDPI · 2021Article
- Abattoir-Based Measures to Assess Swine Welfare: Analysis of the Methods Adopted in European Slaughterhouses.Animals : an open access journal from MDPI · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diseases of the respiratory system are known to negatively impact the profitability of the pig industry, worldwide. Considering the relatively short lifespan of pigs, lesions can be still evident at slaughter, where they can be usefully recorded and scored. Therefore, the slaughterhouse represents a key check-point to assess the health status of pigs, providing unique and valuable feedback to the farm, as well as an important source of data for epidemiological studies. Although relevant, scoring lesions in slaughtered pigs represents a very time-consuming and costly activity, thus making difficult their systematic recording. The present study has been carried out to train a convolutional neural network-based system to automatically score pleurisy in slaughtered pigs. The automation of such a process would be extremely helpful to enable a systematic examination of all slaughtered livestock. Overall, our data indicate that the proposed system is well able to differentiate half carcasses affected with pleurisy from healthy ones, with an overall accuracy of 85.5%. The system was better able to recognize severely affected half carcasses as compared with those showing less severe lesions. The training of convolutional neural networks to identify and score pneumonia, on the one hand, and the achievement of trials in large capacity slaughterhouses, on the other, represent the natural pursuance of the present study. As a result, convolutional neural network-based technologies could provide a fast and cheap tool to systematically record lesions in slaughtered pigs, thus supplying an enormous amount of useful data to all stakeholders in the pig industry.
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Registered trials
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.