The comparison between random forest and boosted trees for dystocia detection in dairy cows

Zaborski, Daniel; Proskura, Witold Stanisław; Grzesiak, Wilhelm; Różańska-Zawieja, Jolanta; Sobek, Z.

doi:10.1016/j.compag.2019.104856

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…(2013) and Zaborski et al. (2019) (0.680–0.711), but it is lower than that determined by Zaborski et al. (2016) (0.827).…”

Section: Discussionmentioning

confidence: 50%

Clinical applicability of external and internal body dimensions in predicting dystocia in late‐gestation Holstein‐Friesian heifers

Nogalski,

Piwczyński,

Nogalska

2023

Reprod Domestic Animals

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The objective of this study was to determine the clinical applicability of maternal intrapelvic area (PA) and selected morphometric parameters that can be measured before parturition in predicting dystocia in dairy heifers. The measurements were performed in 374 late‐gestation Holstein‐Friesian heifers. Inner pelvic height and width were measured using a pelvimeter, and PA was calculated. The heifers were monitored continuously around the time of calving, and calving difficulty was categorized as: unassisted calving (UC), slight assistance (SA), considerable difficulty (CD) and veterinary assistance (VA). Calving performance was analysed with the χ2 test, and the effect of body dimensions on the course of parturition was evaluated by one‐way analysis of variance. Dystocia (CD + VA) was predicted with the use of the classification tree method. Dystocia accounted for 29.14% of all deliveries. The percentages of stillbirths and retained placenta increased (p < .01) with increasing calving difficulty. Average PA immediately before parturition was smaller (p < .01) in group VA (223.2 cm2) than in group UC (253.3 cm2). According to the classification tree, dystocia may occur (74.07% odds) in heifers with PA < 254.2 cm2 and a rump angle <5.68° before parturition. Measurements of heifer's cannon circumference and sire's body size improve the accuracy of dystocia prediction.

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“…(2013) and Zaborski et al. (2019) (0.680–0.711), but it is lower than that determined by Zaborski et al. (2016) (0.827).…”

Section: Discussionmentioning

confidence: 50%

Clinical applicability of external and internal body dimensions in predicting dystocia in late‐gestation Holstein‐Friesian heifers

Nogalski,

Piwczyński,

Nogalska

2023

Reprod Domestic Animals

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“…Zaborski et al [ 73 ] noted that ML offered new ways to detect dystocia and compared the performance of random forest and boosted tree models. Between the two models, boosted trees showed a higher sensitivity for detecting dystocia, but the specificity of the model was too poor to be used in praxis, as it would create too many false alarms [ 73 ]. Therefore, to date, we can see potential opportunities but cannot give reliable practical recommendations.…”

Section: Resultsmentioning

confidence: 99%

“…To respond to it appropriately, it is valuable to detect the condition early. Zaborski et al [73] noted that ML offered new ways to detect dystocia and compared the performance of random forest and boosted tree models. Between the two models, boosted trees showed a higher sensitivity for detecting dystocia, but the specificity of the model was too poor to be used in praxis, as it would create too many false alarms [73].…”

Section: Dystocia and Calvingmentioning

confidence: 99%

Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms

Cockburn

2020

Animals

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Dairy farmers use herd management systems, behavioral sensors, feeding lists, breeding schedules, and health records to document herd characteristics. Consequently, large amounts of dairy data are becoming available. However, a lack of data integration makes it difficult for farmers to analyze the data on their dairy farm, which indicates that these data are currently not being used to their full potential. Hence, multiple issues in dairy farming such as low longevity, poor performance, and health issues remain. We aimed to evaluate whether machine learning (ML) methods can solve some of these existing issues in dairy farming. This review summarizes peer-reviewed ML papers published in the dairy sector between 2015 and 2020. Ultimately, 97 papers from the subdomains of management, physiology, reproduction, behavior analysis, and feeding were considered in this review. The results confirm that ML algorithms have become common tools in most areas of dairy research, particularly to predict data. Despite the quantity of research available, most tested algorithms have not performed sufficiently for a reliable implementation in practice. This may be due to poor training data. The availability of data resources from multiple farms covering longer periods would be useful to improve prediction accuracies. In conclusion, ML is a promising tool in dairy research, which could be used to develop and improve decision support for farmers. As the cow is a multifactorial system, ML algorithms could analyze integrated data sources that describe and ultimately allow managing cows according to all relevant influencing factors. However, both the integration of multiple data sources and the obtainability of public data currently remain challenging.

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“…İneklerin pelvik kanal yapıları, fizyolojik ve metabolik durumları, yetiştirildikleri ortamın çevresel koşulları güç doğum olguları için predispozisyon oluşturmaktadır (2,3). Genel olarak tüm türlerde olduğu gibi ineklerde de güç doğumun genel sebepleri arasında; kalıtsal ve bireye özgü nedenler, çevresel koşullar, beslenme ve bakım koşulları, enfeksiyöz ve travmatik etkenler, kombine veya karışık faktörler şeklinde sıralanabilir (4,5).…”

Section: Introductionunclassified

Normal ve Güç Doğum Yapan İneklerde Bazı Akut Faz Proteinlerinin ve Oksidatif Stres Düzeyinin Belirlenmesi*

Bayyit¹,

Merhan²

2020

Atatürk Üniversitesi Veteriner Bilimleri Dergisi

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Öz: Çok farklı mekanizmalar içeren ve fizyolojik bir süreç olan gebelik, hayvanlarda birçok mekanizmayı etkilemesi nedeniyle, organizmada oluşan akut faz yanıta bağlı olarak akut faz proteinleri (AFP) düzeylerinde artış veya azalışa neden olabilmektedir. Akut faz proteinleri sadece yangısal sürecin teşhis ve prognozunu belirlemek amacıyla değil, aynı zamanda gebelik, doğum, metabolik hastalıklar ve stres gibi yangısal olmayan durumların belirlenmesinde de kullanılabilmektedir. Bu nedenle çalışmanın amacı normal ve güç doğum yapan ineklerde bazı AFP'lerin ve oksidatif stres düzeyinin belirlenmesidir. Çalışmada, 15 adet normal ve 15 adet ise güç doğum yapan Simental ırkı inek kullanıldı. Hayvanların Vena jugularis'inden doğum sonrası (3-48 saat arasında) alınan kanın bir miktarı antikoagulanlı tüplere, kalan kısmı ise antikoagulansız tüplere konuldu. Yapılan analizler sonucunda güç doğum yapan ineklerde haptoglobin, seruloplazmin ve malondialdehidin arttığı, albümin ve redükte glutatyon konsantrasyonunun ise azaldığı belirlendi. Sonuç olarak, yoğun stres altında olan ve müdahale ile doğumu gerçekleşmiş ineklerde, akut faz yanıtın ve oksidatif stresin arttığı görülmüştür. Özellikle güç doğumlarda müdahale yapılan ineklerde enfeksiyon oluşumunu engellemek amacıyla yapılacak uygulamalara ek olarak meydana gelen oksidatif strese karşı antioksidan uygulamaların da faydalı olabileceği kanısına varıldı.

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The comparison between random forest and boosted trees for dystocia detection in dairy cows

Cited by 9 publications

References 28 publications

Clinical applicability of external and internal body dimensions in predicting dystocia in late‐gestation Holstein‐Friesian heifers

Clinical applicability of external and internal body dimensions in predicting dystocia in late‐gestation Holstein‐Friesian heifers

Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms

Normal ve Güç Doğum Yapan İneklerde Bazı Akut Faz Proteinlerinin ve Oksidatif Stres Düzeyinin Belirlenmesi*

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