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Application of Hidden Markov Models and Hidden Semi Markov Models as Diagnostic Aid in Chronic Mastitis in Cows

Safeer M Saifudeen, Ragothaman Venkataramanan, Amaresan Serma Saravana Pandian.


Mastitis is the most important and expensive disease of dairy industry. The present study was conducted at the Large Animal Clinic of Madras Veterinary College Hospital, Chennai to find out the most probable sequence of stages of chronic mastitis. Analysis of HMM and HSMM were performed using ‘The R Project for Statistical Computing’ (version 3.4.0). The study summarized as disease started with stage of Bacterial entry and its flare up (W1) with reduced milk production and presence of watery milk from the lactating quarters. As the time advanced, the disease progressed to the stage of increasing somatic cell count (W2) where repeated episodes of sub acute mastitis could be seen. The stage of fibrous tissue proliferation is visible only in the case of hidden semi Markov model (HSMM). These models might be used in decision making process like, either maintenance or culling of the affected animals in established farms.

Key words: Hidden Markov Model, Hidden Semi Markov Model, Chronic Mastitis, Inflammation, Symptoms.

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