156 related articles for article (PubMed ID: 32961892)
1. Analysis of Cattle Social Transitional Behaviour: Attraction and Repulsion.
Xu H; Li S; Lee C; Ni W; Abbott D; Johnson M; Lea JM; Yuan J; Campbell DLM
Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32961892
[TBL] [Abstract][Full Text] [Related]
2. Sheep's coping style can be identified by unsupervised machine learning from unlabeled data.
Çakmakçı C
Behav Processes; 2022 Jan; 194():104559. PubMed ID: 34838901
[TBL] [Abstract][Full Text] [Related]
3. Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach.
Pontin F; Lomax N; Clarke G; Morris MA
Int J Environ Res Public Health; 2021 Oct; 18(21):. PubMed ID: 34769991
[TBL] [Abstract][Full Text] [Related]
4. Herd clustering strategies and corresponding genetic evaluations based on social-ecological characteristics for a local endangered cattle breed.
Herold J; Brügemann K; König S
Arch Anim Breed; 2021; 64(1):187-198. PubMed ID: 34109268
[TBL] [Abstract][Full Text] [Related]
5. Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches.
McVey C; Hsieh F; Manriquez D; Pinedo P; Horback K
Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009546
[TBL] [Abstract][Full Text] [Related]
6. Using unsupervised learning to classify inlet water for more stable design of water reuse in industrial parks.
Chen K; Shi X; Zhang Z; Chen S; Ma J; Zheng T; Alfonso L
Water Sci Technol; 2024 Apr; 89(7):1757-1770. PubMed ID: 38619901
[TBL] [Abstract][Full Text] [Related]
7. Clinical fracture risk evaluated by hierarchical agglomerative clustering.
Kruse C; Eiken P; Vestergaard P
Osteoporos Int; 2017 Mar; 28(3):819-832. PubMed ID: 27848006
[TBL] [Abstract][Full Text] [Related]
8. Machine Learning Assisted Clustering of Nanoparticle Structures.
Roncaglia C; Ferrando R
J Chem Inf Model; 2023 Jan; 63(2):459-473. PubMed ID: 36597194
[TBL] [Abstract][Full Text] [Related]
9. Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials.
Sinha P; Spicer A; Delucchi KL; McAuley DF; Calfee CS; Churpek MM
EBioMedicine; 2021 Dec; 74():103697. PubMed ID: 34861492
[TBL] [Abstract][Full Text] [Related]
10. Feature selection for unsupervised machine learning of accelerometer data physical activity clusters - A systematic review.
Jones PJ; Catt M; Davies MJ; Edwardson CL; Mirkes EM; Khunti K; Yates T; Rowlands AV
Gait Posture; 2021 Oct; 90():120-128. PubMed ID: 34438293
[TBL] [Abstract][Full Text] [Related]
11. Unsupervised machine learning methods and emerging applications in healthcare.
Eckhardt CM; Madjarova SJ; Williams RJ; Ollivier M; Karlsson J; Pareek A; Nwachukwu BU
Knee Surg Sports Traumatol Arthrosc; 2023 Feb; 31(2):376-381. PubMed ID: 36378293
[TBL] [Abstract][Full Text] [Related]
12. Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence.
Brito da Silva LE; Elnabarawy I; Wunsch DC
Neural Netw; 2020 Jan; 121():208-228. PubMed ID: 31574412
[TBL] [Abstract][Full Text] [Related]
13. Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California.
McMahon ME; Doroshenko L; Roostaei J; Cho H; Haider MA
Health Care Manag Sci; 2022 Dec; 25(4):574-589. PubMed ID: 35732967
[TBL] [Abstract][Full Text] [Related]
14. Applying Machine Learning Algorithms to Segment High-Cost Patient Populations.
Yan J; Linn KA; Powers BW; Zhu J; Jain SH; Kowalski JL; Navathe AS
J Gen Intern Med; 2019 Feb; 34(2):211-217. PubMed ID: 30543022
[TBL] [Abstract][Full Text] [Related]
15. Does Determination of Initial Cluster Centroids Improve the Performance of
Pourahmad S; Basirat A; Rahimi A; Doostfatemeh M
Comput Math Methods Med; 2020; 2020():7636857. PubMed ID: 32802153
[TBL] [Abstract][Full Text] [Related]
16. Can unsupervised learning methods applied to milk recording big data provide new insights into dairy cow health?
Franceschini S; Grelet C; Leblois J; Gengler N; Soyeurt H;
J Dairy Sci; 2022 Aug; 105(8):6760-6772. PubMed ID: 35773033
[TBL] [Abstract][Full Text] [Related]
17. Molecular descriptor analysis of approved drugs using unsupervised learning for drug repurposing.
Madugula SS; John L; Nagamani S; Gaur AS; Poroikov VV; Sastry GN
Comput Biol Med; 2021 Nov; 138():104856. PubMed ID: 34555571
[TBL] [Abstract][Full Text] [Related]
18. Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool.
Celecia A; Figueiredo K; Rodriguez C; Vellasco M; Maldonado E; Silva MA; Rodrigues A; Nascimento R; Ourofino C
Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640667
[TBL] [Abstract][Full Text] [Related]
19. On the Behaviour of K-Means Clustering of a Dissimilarity Matrix by Means of Full Multidimensional Scaling.
Vera JF; Macías R
Psychometrika; 2021 Jun; 86(2):489-513. PubMed ID: 34008128
[TBL] [Abstract][Full Text] [Related]
20. A density-based competitive data stream clustering network with self-adaptive distance metric.
Xu B; Shen F; Zhao J
Neural Netw; 2019 Feb; 110():141-158. PubMed ID: 30557793
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
