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kmeans function in matlab  (MathWorks Inc)


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    MathWorks Inc kmeans function in matlab
    Kmeans Function In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2368 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/kmeans+function/Statistics+and+Machine+Learning+Toolbox/pmc12961308-213-5-8
    Average 96 stars, based on 2368 article reviews
    kmeans function in matlab - by Bioz Stars, 2026-11
    96/100 stars

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    Article Title: Impaired folate metabolism reshapes auditory response profiles and impairs loudness perception in MTHFR-deficient mice.
    Article Snippet: Folate metabolism, regulated by methylenetetrahydrofolate reductase (MTHFR), is crucial for proper neurodevelopment, and disruptions—whether due to genetic polymorphisms or maternal nutritional deficits—have been linked to cognitive and behavioral impairments.. Notably, MTHFR-deficient mouse models display altered social interaction and auditory communication, hinting at disruptions in auditory-related circuits and prompting the question of whether impaired folate metabolism might also affect sound processing and perception.. Here, using two-photon calcium imaging, we show that MTHFR deficiency increases both spontaneous and soundevoked activity in the auditory cortex and significantly shifts neuronal response profiles, which in turn elevates perceived loudness while reducing sound-level discrimination.

    Article Title: Fluorinated elastomers for brain probes and other applications
    Article Snippet: MATLAB's “kmeans” function was used to cluster the extracted waveforms and to exclude noise artefacts.

    Article Title: To Acquire or Not to Acquire: Evaluating Compressive Sensing for Raman Spectroscopy in Biology.
    Article Snippet: In this work, we implemented k-means clustering by using kmeans function in MATLAB on a PC score data set of the top 10 PC components obtained from tissue Raman spectra.

    Article Title: NaDyNet: A toolbox for dynamic network analysis of naturalistic stimuli.
    Article Snippet: MATLAB’s kmeans function provides several methods for determining the distance between clusters.

    Article Title: Identification of digital twins to guide interpretable AI for diagnosis and prognosis in heart failure
    Article Snippet: K-means was performed with MATLAB’s built-in kmeans function, while hierarchical clustering was conducted using the cluster function, which implements bottom-up clustering.

    Article Title: Demixing and Analysis of Complex Biological Raman Hyperspectra Based on Peak Fitting, Amplitude Trend Clustering, and Spectrum Reconstruction.
    Article Snippet: To better interpret the Raman spectra from mammalian cells, it is often desirable to reduce their complexity by decomposing them into the spectral contributions from individual macromolecules or types of macromolecules.. Diverse methods exist for demixing complex spectra, each with different benefits and drawbacks.. However, some methods require a library of component spectra that might not be available, while others are hampered by noise and peak congestion that includes many proximal overlapping peaks.

    Article Title: Stable phytoplankton community compositions in Lake Mead (Nevada-Arizona, USA) during two decades of severe drought
    Article Snippet: Lake Mead, a large reservoir on the Colorado River and a critical drinking water source for the southwestern United States, typically exhibits high water quality, characterized by low nutrient and chlorophyll-a concentrations.. This stability persists despite the inflow of highly treated wastewater since the 1960s and significant water level declines since 2000, driven by the ongoing Megadrought and basinwide consumptive use.. Such environmental changes may alter phytoplankton communities, potentially leading to increased cyanobacteria abundance, which could negatively impact water quality and the aquatic ecosystem through harmful algal blooms and toxin production.

    Article Title: Deciphering the Heterogeneity of Schizophrenia: A Multimodal and Multivariate Neuroimaging Framework for Unveiling Brain-Symptom Relationships and Underlying Subtypes.
    Article Snippet: © The Author(s) 2025.. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.. All rights reserved.



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