These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 38756684)

  • 1. Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration.
    Dunford CE; Marks NJ; Wilson RP; Scantlebury DM
    Ecol Evol; 2024 May; 14(5):e11380. PubMed ID: 38756684
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Cats (
    Smit M; Ikurior SJ; Corner-Thomas RA; Andrews CJ; Draganova I; Thomas DG
    Sensors (Basel); 2023 Aug; 23(16):. PubMed ID: 37631701
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Limitations of using surrogates for behaviour classification of accelerometer data: refining methods using random forest models in Caprids.
    Dickinson ER; Twining JP; Wilson R; Stephens PA; Westander J; Marks N; Scantlebury DM
    Mov Ecol; 2021 Jun; 9(1):28. PubMed ID: 34099067
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Using tri-axial accelerometer loggers to identify spawning behaviours of large pelagic fish.
    Clarke TM; Whitmarsh SK; Hounslow JL; Gleiss AC; Payne NL; Huveneers C
    Mov Ecol; 2021 May; 9(1):26. PubMed ID: 34030744
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Behavioral classification of low-frequency acceleration and temperature data from a free-ranging small mammal.
    Studd EK; Landry-Cuerrier M; Menzies AK; Boutin S; McAdam AG; Lane JE; Humphries MM
    Ecol Evol; 2019 Jan; 9(1):619-630. PubMed ID: 30680142
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quantifying finer-scale behaviours using self-organising maps (SOMs) to link accelerometery signatures with behavioural patterns in free-roaming terrestrial animals.
    Galea N; Murphy F; Gaschk JL; Schoeman DS; Clemente CJ
    Sci Rep; 2021 Jun; 11(1):13566. PubMed ID: 34193910
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using accelerometers to develop time-energy budgets of wild fur seals from captive surrogates.
    Ladds MA; Salton M; Hocking DP; McIntosh RR; Thompson AP; Slip DJ; Harcourt RG
    PeerJ; 2018; 6():e5814. PubMed ID: 30386705
    [TBL] [Abstract][Full Text] [Related]  

  • 8. High accuracy at low frequency: detailed behavioural classification from accelerometer data.
    Tatler J; Cassey P; Prowse TAA
    J Exp Biol; 2018 Nov; 221(Pt 23):. PubMed ID: 30322979
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Categorising cheetah behaviour using tri-axial accelerometer data loggers: a comparison of model resolution and data logger performance.
    McGowan NE; Marks NJ; Maule AG; Schmidt-Küntzel A; Marker LL; Scantlebury DM
    Mov Ecol; 2022 Feb; 10(1):7. PubMed ID: 35123592
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Assessment of Machine Learning Models to Identify Port Jackson Shark Behaviours Using Tri-Axial Accelerometers.
    Kadar JP; Ladds MA; Day J; Lyall B; Brown C
    Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33322308
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data.
    Jeantet L; Dell'Amico F; Forin-Wiart MA; Coutant M; Bonola M; Etienne D; Gresser J; Regis S; Lecerf N; Lefebvre F; de Thoisy B; Le Maho Y; Brucker M; Châtelain N; Laesser R; Crenner F; Handrich Y; Wilson R; Chevallier D
    J Exp Biol; 2018 May; 221(Pt 10):. PubMed ID: 29661804
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Classification of broiler behaviours using triaxial accelerometer and machine learning.
    Yang X; Zhao Y; Street GM; Huang Y; Filip To SD; Purswell JL
    Animal; 2021 Jul; 15(7):100269. PubMed ID: 34102430
    [TBL] [Abstract][Full Text] [Related]  

  • 13. On the use of on-cow accelerometers for the classification of behaviours in dairy barns.
    Benaissa S; Tuyttens FAM; Plets D; de Pessemier T; Trogh J; Tanghe E; Martens L; Vandaele L; Van Nuffel A; Joseph W; Sonck B
    Res Vet Sci; 2019 Aug; 125():425-433. PubMed ID: 29174287
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Increasingly detailed insights in animal behaviours using continuous on-board processing of accelerometer data.
    Yu H; Klaassen CAJ; Deng J; Leen T; Li G; Klaassen M
    Mov Ecol; 2022 Oct; 10(1):42. PubMed ID: 36280879
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Pilot Study Using Accelerometers to Characterise the Licking Behaviour of Penned Cattle at a Mineral Block Supplement.
    Simanungkalit G; Barwick J; Cowley F; Dobos R; Hegarty R
    Animals (Basel); 2021 Apr; 11(4):. PubMed ID: 33920600
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Digging into the behaviour of an active hunting predator: arctic fox prey caching events revealed by accelerometry.
    Clermont J; Woodward-Gagné S; Berteaux D
    Mov Ecol; 2021 Nov; 9(1):58. PubMed ID: 34838144
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development of a multisensor biologging collar and analytical techniques to describe high-resolution spatial behavior in free-ranging terrestrial mammals.
    Painter MS; Silovský V; Blanco J; Holton M; Faltusová M; Wilson R; Börger L; Psotta L; Ramos-Almodovar F; Estrada L; Landler L; Malkemper P; Hart V; Ježek M
    Ecol Evol; 2024 Sep; 14(9):e70264. PubMed ID: 39318532
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours.
    Ladds MA; Thompson AP; Slip DJ; Hocking DP; Harcourt RG
    PLoS One; 2016; 11(12):e0166898. PubMed ID: 28002450
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Behavioural compass: animal behaviour recognition using magnetometers.
    Chakravarty P; Maalberg M; Cozzi G; Ozgul A; Aminian K
    Mov Ecol; 2019; 7():28. PubMed ID: 31485331
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Training in the Dark: Using Target Training for Non-Invasive Application and Validation of Accelerometer Devices for an Endangered Primate (
    Nekaris KA; Campera M; Chimienti M; Murray C; Balestri M; Showell Z
    Animals (Basel); 2022 Feb; 12(4):. PubMed ID: 35203119
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.