Abstract
Lumpy skin disease is an infectious disease in cattle caused by a virus. It has enormous cattle loss due to improper disease diagnosis. The disability of cattle to express pain caused by this disease leads to ignorance and the spread of this disease. This disease may also lead to fatality in some cases. Hence, proper precautions must be taken against the spread. Through manual observation, veterinary doctors generally detect Lumpy Skin Disease. However, it is not possible to detect it in the early stage using manual methods. In these cases, AI-based methods achieve higher accuracy in disease prediction. Here, a Random Forest-based machine learning model is used to detect lumpy skin disease. The data used for training and validation of lumpy skin disease available on Kaggle is used. The proposed model has shown an accuracy of 98%.
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Patel, S., Thakkar, V., Swain, D., Bhilare, A. (2024). An Early Lumpy Skin Disease Detection System Using Machine Learning. In: Shukla, S., Sayama, H., Kureethara, J.V., Mishra, D.K. (eds) Data Science and Security. IDSCS 2023. Lecture Notes in Networks and Systems, vol 922. Springer, Singapore. https://doi.org/10.1007/978-981-97-0975-5_4
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DOI: https://doi.org/10.1007/978-981-97-0975-5_4
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