Discrete Homogeneous and Non-Homogeneous Markov Chains Enhance Predictive Modelling for Dairy Cow Diseases

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F24%3A98108" target="_blank" >RIV/60460709:41110/24:98108 - isvavai.cz</a>

Alternative codes found

RIV/60460709:41210/24:98108

Result on the web

<a href="https://www.mdpi.com/2076-2615/14/17/2542" target="_blank" >https://www.mdpi.com/2076-2615/14/17/2542</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ani14172542" target="_blank" >10.3390/ani14172542</a>

Result language

angličtina

Original language name

Discrete Homogeneous and Non-Homogeneous Markov Chains Enhance Predictive Modelling for Dairy Cow Diseases

Original language description

Modelling and predicting dairy cow diseases empowers farmers with valuable information for herd health management, thereby decreasing costs and increasing profits. For this purpose, predictive models were developed based on machine learning algorithms. However, machine-learning based approaches require the development of a specific model for each disease, and their consistency is limited by low farm data availability. To overcome this lack of complete and accurate data, we developed a predictive model based on discrete Homogeneous and Non-homogeneous Markov chains. After aggregating data into categories, we developed a method for defining the adequate number of Markov chain states. Subsequently, we selected the best prediction model through Chebyshev distance minimization. For 14 of 19 diseases, less than 15% maximum differences were measured between the last month of actual and predicted disease data. This model can be easily implemented in low-tech dairy farms to project costs with antibiotics and other treatments. Furthermore, the model’s adaptability allows it to be extended to other disease types or conditions with minimal adjustments. Therefore, including this predictive model for dairy cow diseases in decision support systems may enhance herd health management and streamline the design of evidence-based farming strategies.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

40101 - Agriculture

Project

<a href="/en/project/QK22010270" target="_blank" >QK22010270: Management optimalization of individual reproduction performance in dairy cattle</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Animals

ISSN

2076-2615

e-ISSN

2076-2615

Volume of the periodical

14

Issue of the periodical within the volume

17

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

1-16

UT code for WoS article

001311127800001

EID of the result in the Scopus database

2-s2.0-85203653836