Artículo

Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach

Resumen

Mastitis, an important disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for adequate control. Studies using artificial intelligence (AI) models to classify, identify, predict, and diagnose mastitis show promise in improving mastitis control. This bibliometric review aimed to evaluate AI and bovine mastitis terms in the most relevant Scopus-indexed papers from 2011 to 2021. Sixty-two documents were analyzed, revealing key terms, prominent researchers, relevant publications, main themes, and keyword clusters. “Mastitis” and “machine learning” were the most cited terms, with an increasing trend from 2018 to 2021. Other terms, such as “sensors” and “mastitis detection”, also emerged. The United States was the most cited country and presented the largest collaboration network. Publications on mastitis and AI models notably increased from 2016 to 2021, indicating growing interest. However, few studies utilized AI for bovine mastitis detection, primarily employing artificial neural network models. This suggests a clear potential for further research in this area.
Autores
Pugas, MAR; Lopes, EL; Lopes, EH; Ferreira, HL
Título
From One End to The Other: A Bibliometric Study of Publications on Omission Neglect Based on The Journals Between 1988 and 2016
Afiliaciones
Universidade Nove de Julho
Año
2020
DOI
10.23925/2178-0080.2020v22i1.44752
Tipo de acceso abierto
gold, Green Submitted
Referencia
WOS:000543784400006
Artículo obtenido de:
WOS
Fuente
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