Risk prediction model of clinical mastitis in lactating dairy cows based on machine learning algorithms
出版年份 2023 全文链接
标题
Risk prediction model of clinical mastitis in lactating dairy cows based on machine learning algorithms
作者
关键词
-
出版物
PREVENTIVE VETERINARY MEDICINE
Volume -, Issue -, Pages 106059
出版商
Elsevier BV
发表日期
2023-10-28
DOI
10.1016/j.prevetmed.2023.106059
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Multivariable time series classification for clinical mastitis detection and prediction in automated milking systems
- (2023) X. Fan et al. JOURNAL OF DAIRY SCIENCE
- Recent advances in decision trees: an updated survey
- (2022) Vinícius G. Costa et al. ARTIFICIAL INTELLIGENCE REVIEW
- Prediction of the durability of high-performance concrete using an integrated RF-LSSVM model
- (2022) Yang Liu et al. CONSTRUCTION AND BUILDING MATERIALS
- Early detection of mastitis in cows using the system based on 3D motions detectors
- (2022) Grzegorz Grodkowski et al. Scientific Reports
- Exploring machine learning algorithms for early prediction of clinical mastitis
- (2021) Liliana Fadul-Pacheco et al. INTERNATIONAL DAIRY JOURNAL
- Milk losses linked to mastitis treatments at dairy farms with automatic milking systems
- (2021) Ines Adriaens et al. PREVENTIVE VETERINARY MEDICINE
- Machine learning based fog computing assisted data-driven approach for early lameness detection in dairy cattle
- (2020) Mohit Taneja et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Automated prediction of mastitis infection patterns in dairy herds using machine learning
- (2020) Robert M. Hyde et al. Scientific Reports
- Synthetic minority oversampling of vital statistics data with generative adversarial networks
- (2020) Aki Koivu et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Predicting dairy cattle heat stress using machine learning techniques
- (2020) C.A. Becker et al. JOURNAL OF DAIRY SCIENCE
- Epidemiology and Classification of Mastitis
- (2020) Maros Cobirka et al. Animals
- Application of machine learning to improve dairy farm management: A systematic literature review
- (2020) Naftali Slob et al. PREVENTIVE VETERINARY MEDICINE
- Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models
- (2019) Mansour Ebrahimi et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Comparing regression, naive Bayes, and random forest methods in the prediction of individual survival to second lactation in Holstein cattle
- (2019) E.M.M. van der Heide et al. JOURNAL OF DAIRY SCIENCE
- Ranking of environmental heat stressors for dairy cows using machine learning algorithms
- (2019) Michael T. Gorczyca et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Ability of milk pH to predict subclinical mastitis and intramammary infection in quarters from lactating dairy cattle
- (2018) S.A. Kandeel et al. JOURNAL OF DAIRY SCIENCE
- A 100-Year Review: Mastitis detection, management, and prevention
- (2017) Pamela L. Ruegg JOURNAL OF DAIRY SCIENCE
- Incidence of clinical mastitis and distribution of pathogens on large Chinese dairy farms
- (2017) Jian Gao et al. JOURNAL OF DAIRY SCIENCE
- Bayesian integration of sensor information and a multivariate dynamic linear model for prediction of dairy cow mastitis
- (2016) Dan B. Jensen et al. JOURNAL OF DAIRY SCIENCE
- The cost of clinical mastitis in the first 30 days of lactation: An economic modeling tool
- (2015) E. Rollin et al. PREVENTIVE VETERINARY MEDICINE
- Sensors and Clinical Mastitis—The Quest for the Perfect Alert
- (2010) Henk Hogeveen et al. SENSORS
- AUC: a misleading measure of the performance of predictive distribution models
- (2007) Jorge M. Lobo et al. GLOBAL ECOLOGY AND BIOGEOGRAPHY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search