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Mastitis is one of the most significant health challenges faced by dairy animals, including cows and buffaloes. Recent advances in technology and data analysis have opened up new possibilities for detecting and predicting the onset of the disease in advance. In this review, we aim to provide insights into the current state of research on this persistent challenge in dairy production, focusing on studies published in 2023 and later. In particular, we examine recent developments in the application of machine learning models for subclinic mastitis detection, analyzing their methodologies, datasets, and results.

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Machine Learning Approaches for Detecting Subclinical Mastitis in Dairy Animals: A Brief Review of Recent Literature

  • 会议论文

  • 发表日期：

    2025年

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  • Alessandra Amato,
  • Francesco Bonavolontà,
  • Mattia Fonisto,
  • Maria Teresa Verde

摘要

Mastitis is one of the most significant health challenges faced by dairy animals, including cows and buffaloes. Recent advances in technology and data analysis have opened up new possibilities for detecting and predicting the onset of the disease in advance. In this review, we aim to provide insights into the current state of research on this persistent challenge in dairy production, focusing on studies published in 2023 and later. In particular, we examine recent developments in the application of machine learning models for subclinic mastitis detection, analyzing their methodologies, datasets, and results.