Bayesian latent class models to determine diagnostic sensitivities and specificities of two point of care rapid tests (Selma plus, Dipslide) for the detection of milk pathogens associated with mastitis in dairy cows

Rediger, David (2023). Bayesian latent class models to determine diagnostic sensitivities and specificities of two point of care rapid tests (Selma plus, Dipslide) for the detection of milk pathogens associated with mastitis in dairy cows. (Dissertation, Wiederkäuerklink, DKV, Vetsuisse Fakultät)

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Development and validations of accurate mastitis diagnostics are crucial to make timely and evidence-based decisions on mastitis therapy in order to reduce its impact on productivity, animal welfare and practicing the prudent use of antimicrobials on dairy farms.

Item Type:

Thesis (Dissertation)

Division/Institute:

05 Veterinary Medicine > Department of Clinical Veterinary Medicine (DKV)
05 Veterinary Medicine > Department of Clinical Veterinary Medicine (DKV) > Clinic for Ruminants

UniBE Contributor:

Rediger, David, Bodmer, Michèle

Subjects:

500 Science > 590 Animals (Zoology)
600 Technology > 610 Medicine & health
600 Technology > 630 Agriculture

Language:

English

Submitter:

Nathalie Viviane Zollinger

Date Deposited:

10 Nov 2023 07:52

Last Modified:

21 Nov 2023 14:34

URI:

https://boris.unibe.ch/id/eprint/188759

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