Hassan, F.A.M., Moawed, S.A., El-Araby, I.E., & Gouda, H.F. (2022). Machine Learning Based Prediction for Solving Veterinary Data Problems: A Review. Journal of Advanced Veterinary Research. Veterinary Medicine and the Concept of One Health, 12(6).
This review explores the potential of machine learning (ML) in predicting and solving veterinary data problems. It highlights the advantages of ML over traditional statistical models, particularly in disease prediction where statistical models often suffer from high bias and decreased reliability. The review addresses challenges in ML implementation, including data size, algorithm tuning, and feature selection, that affect the development of accurate predictive models. The authors encourage increased application of ML in veterinary medicine to improve decision-making and overcome the limitations of conventional methods.
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