Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models-Reference-Cited by-同舟云学术

Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models

Published:2019-11 Issue: Volume:114 Page:103456
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Ebrahimi Mansour,Mohammadi-Dehcheshmeh Manijeh,Ebrahimie Esmaeil,Petrovski Kiro R.

Funder

the National Collaborative Research Infrastructure Strategy

University of Adelaide

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference27 articles.

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3. Methicillin-resistant Staphylococcus aureus (MRSA) ST398 associated with clinical and subclinical mastitis in Belgian cows;Vanderhaeghen;Vet. Microbiol.,2010

4. Field trial of a staphylococcal mastitis vaccine in dairy herds: clinical, subclinical and microbiological assessments;Watson;Aust. Vet. J.,1996

5. Prediction of intramammary infection status across the dry period from lifetime cow records;Henderson;J. Dairy Sci.,2016

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