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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Exploring machine learning algorithms for early prediction of clinical mastitis
Liliana Fadul-Pacheco, Hector Delgado, Víctor E. Cabrera
International Dairy Journal (2021) Vol. 119, pp. 105051-105051
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

The Prediction of Clinical Mastitis in Dairy Cows Based on Milk Yield, Rumination Time, and Milk Electrical Conductivity Using Machine Learning Algorithms
Hong Tian, Xiaojing Zhou, Hao Wang, et al.
Animals (2024) Vol. 14, Iss. 3, pp. 427-427
Open Access | Times Cited: 12
Performance comparison of machine learning models used for predicting subclinical mastitis in dairy cows: Bagging, boosting, stacking, and super-learner ensembles versus single machine learning models
Alicja Satoła, Krzysztof Satoła
Journal of Dairy Science (2024) Vol. 107, Iss. 6, pp. 3959-3972
Open Access | Times Cited: 11
Standardization for Data Generation and Collection in the Dairy Industry: Addressing Challenges and Charting a Path Forward
M. Baldin, J.M. Bewley, Víctor E. Cabrera, et al.
Animals (2025) Vol. 15, Iss. 2, pp. 250-250
Open Access | Times Cited: 1
The Early Prediction of Common Disorders in Dairy Cows Monitored by Automatic Systems with Machine Learning Algorithms
Xiaojing Zhou, Chuang Xu, Hao Wang, et al.
Animals (2022) Vol. 12, Iss. 10, pp. 1251-1251
Open Access | Times Cited: 37
Future of dairy farming from the Dairy Brain perspective: Data integration, analytics, and applications
Víctor E. Cabrera, Liliana Fadul-Pacheco
International Dairy Journal (2021) Vol. 121, pp. 105069-105069
Open Access | Times Cited: 37
Digitalization of livestock farms through blockchain, big data, artificial intelligence, and Internet of Things
Rajneesh Thakur, Manoj Baghel, Suvarna Bhoj, et al.
Elsevier eBooks (2024), pp. 179-206
Closed Access | Times Cited: 5
Novel ways to use sensor data to improve mastitis management
H. Hogeveen, Ilka Christine Klaas, Gunnar Dalen, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 10, pp. 11317-11332
Open Access | Times Cited: 27
Economic and Environmental Benefits of Digital Agricultural Technological Solutions in Livestock Farming: A Review
George Papadopoulos, Maria-Zoi Papantonatou, Havva Uyar, et al.
Smart Agricultural Technology (2025), pp. 100783-100783
Open Access
Mastitis diagnosis with machine learning algorithms
Adnan Kalkan, Mehmet Tepeli, Aslı Göde
Neural Computing and Applications (2025)
Open Access
Machine Learning Approaches for Detecting Subclinical Mastitis in Dairy Animals: A Brief Review of Recent Literature
Alessandra Amato, Francesco Bonavolontà, Mattia Fonisto, et al.
Lecture notes on data engineering and communications technologies (2025), pp. 1-7
Closed Access
Delineating Mastitis Cases in Dairy Cows: Development of an IoT-Enabled Intelligent Decision Support System for Dairy Farms
Mohammad Farhan Khan, V.M. Thorup, Zhenhua Luo
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 7, pp. 9508-9517
Open Access | Times Cited: 3
Entire-barn dairy cow tracking framework for multi-camera systems
Yota Yamamoto, Kazuhiro Akizawa, S. Aou, et al.
Computers and Electronics in Agriculture (2024) Vol. 229, pp. 109668-109668
Open Access | Times Cited: 3
MasPA: A Machine Learning Application to Predict Risk of Mastitis in Cattle from AMS Sensor Data
Naeem Abdul Ghafoor, Beata Sitkowska
AgriEngineering (2021) Vol. 3, Iss. 3, pp. 575-583
Open Access | Times Cited: 21
Optimized Deep-Learning-Based Method for Cattle Udder Traits Classification
Hina Afridi, Mohib Ullah, Øyvind Nordbø, et al.
Mathematics (2022) Vol. 10, Iss. 17, pp. 3097-3097
Open Access | Times Cited: 14
Multivariable time series classification for clinical mastitis detection and prediction in automated milking systems
Xinxin Fan, R.D. Watters, D.V. Nydam, et al.
Journal of Dairy Science (2023) Vol. 106, Iss. 5, pp. 3448-3464
Open Access | Times Cited: 8
The Use of Machine Learning to Predict Prevalence of Subclinical Mastitis in Dairy Sheep Farms
Yiannis Kiouvrekis, Natalia G. C. Vasileiou, Eleni I. Katsarou, et al.
Animals (2024) Vol. 14, Iss. 16, pp. 2295-2295
Open Access | Times Cited: 2
Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach
Thatiane Mendes Mitsunaga, Breno Luís Nery Garcia, Ligia Beatriz Rizzanti Pereira, et al.
Animals (2024) Vol. 14, Iss. 14, pp. 2023-2023
Open Access | Times Cited: 2
A review and future trends of precision livestock over dairy and beef cow cattle with artificial intelligence
Álvaro Michelena, Óscar Fontenla-Romero, José Luis Calvo‐Rolle
Logic Journal of IGPL (2024)
Open Access | Times Cited: 2
Risk prediction model of clinical mastitis in lactating dairy cows based on machine learning algorithms
Wenkuo Luo, Qiang Dong, Feng Yan
Preventive Veterinary Medicine (2023) Vol. 221, pp. 106059-106059
Closed Access | Times Cited: 5
Augmenting Tele-Postpartum Care with Vision-Based Detection of Breastfeeding-related Conditions: Algorithm Development and Validation (Preprint)
Jéssica de Souza, Varun Viswanath, Jessica Maria Echterhoff, et al.
JMIR AI (2024) Vol. 3, pp. e54798-e54798
Open Access | Times Cited: 1
Classification of Livestock Diseases Using Machine Learning Algorithms
G. Hannah Grace, Nivetha Martin, I. Pradeepa, et al.
(2024), pp. 127-138
Closed Access | Times Cited: 1
Artificial intelligence applied to dairy science: insights from the Dairy Brain Initiative
Víctor E. Cabrera
Animal Frontiers (2024) Vol. 14, Iss. 6, pp. 60-63
Open Access | Times Cited: 1
MILK LIPIDS AND SUBCLINICAL MASTITIS
В. В. Данчук, В. Ushkalov, С. В. Мидык, et al.
Food Science and Technology (2021) Vol. 15, Iss. 2
Open Access | Times Cited: 9
The Relationship between Reticuloruminal Temperature, Reticuloruminal pH, Cow Activity, and Clinical Mastitis in Dairy Cows
Ramūnas Antanaitis, Lina Anskienė, Giedrius Palubinskas, et al.
Animals (2023) Vol. 13, Iss. 13, pp. 2134-2134
Open Access | Times Cited: 3
Improving farm decisions: The application of data engineering techniques to manage data streams from contemporary dairy operations
Steven R. Wangen, Fan Zhang, Liliana Fadul-Pacheco, et al.
Livestock Science (2021) Vol. 250, pp. 104602-104602
Open Access | Times Cited: 6
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