ReviewAnimals : an open access journal from MDPI2025
The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review.
Review in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Machine learning based detection of subacute ruminal acidosis in early lactation dairy cows using multi-sensor behavioral, physiological, and milk production data.Scientific reports · 2026Article
- Integrating biomarkers and artificial intelligence for precision diagnostics in cattle health and herd management: a review.Veterinary research communications · 2026Review
- Big data and artificial intelligence in animal nutrition: a new era of precision feeding.Tropical animal health and production · 2026Review
- From machine learning to digital twin integration for livestock production and research.Frontiers in veterinary science · 2026Review
- Milk Biomarkers and Herd Welfare Status in Dairy Cattle: A Machine Learning Approach.Veterinary sciences · 2025Article
- Preventive Immunology for Livestock and Zoonotic Infectious Diseases in the One Health Era: From Mechanistic Insights to Innovative Interventions.Veterinary sciences · 2025Review
- The Impact of Heat Stress on Dairy Cattle: Effects on Milk Quality, Rumination Behaviour, and Reticulorumen pH Response Using Machine Learning Models.Biosensors · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020-2024). A description of ML methods (linear and logistic regression, classification and regression trees, chi-squared automatic interaction detection, random forest, AdaBoost, support vector machines, k-nearest neighbors, naive Bayes classifier, multivariate adaptive regression splines, artificial neural networks, including deep neural networks and convolutional neural networks, as well as Gaussian mixture models and cluster analysis), with some examples of their application in various aspects of dairy cattle breeding and husbandry, is provided. In addition, the stages of model construction and implementation, as well as the performance indicators for regression and classification models, are described. Finally, time trends in the popularity of ML methods in dairy cattle farming are briefly discussed.
Indexed as
Identifiers
What OpenQuestion holds
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.