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Multinomial logistic regression based on neural networks reveals inherent differences among dairy farms depending on the differential exposure to Fasciola hepatica and Ostertagia ostertagi


Oehm, Andreas W; Leinmueller, Markus; Zablotski, Yury; Campe, Amely; Hoedemaker, Martina; Springer, Andrea; Jordan, Daniela; Strube, Christina; Knubben-Schweizer, Gabriela (2023). Multinomial logistic regression based on neural networks reveals inherent differences among dairy farms depending on the differential exposure to Fasciola hepatica and Ostertagia ostertagi. International Journal for Parasitology, 53(11-12):687-697.

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Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Veterinärwissenschaftliches Institut > Institute of Parasitology
04 Faculty of Medicine > Institute of Parasitology
Dewey Decimal Classification:610 Medicine & health
600 Technology
570 Life sciences; biology
Scopus Subject Areas:Life Sciences > Parasitology
Health Sciences > Infectious Diseases
Uncontrolled Keywords:Infectious Diseases, Parasitology
Language:English
Date:1 October 2023
Deposited On:17 Feb 2024 17:34
Last Modified:30 Jun 2024 03:31
Publisher:Elsevier
ISSN:0020-7519
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1016/j.ijpara.2023.05.006
PubMed ID:37355196
Project Information:
  • : FunderBundesministerium für Ernährung und Landwirtschaft
  • : Grant ID
  • : Project Title
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)