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matlab software calculations  (MathWorks Inc)


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    MathWorks Inc matlab software calculations
    Matlab Software Calculations, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 324 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/matlab-based+data+analysis+tool/MATLAB+Compiler/10__62535_slash_qvk7py59-40-9-9
    Average 96 stars, based on 324 article reviews
    matlab software calculations - by Bioz Stars, 2026-09
    96/100 stars

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    other:

    Article Title: An Integrated Framework for Automated Image Segmentation and Personalized Wall Stress Estimation of Abdominal Aortic Aneurysms.
    Article Snippet: The script can be compiled into a standalone executable (e.g., via MATLAB Compiler) that runs with the free MATLAB Runtime, so end users do not require a MATLAB license [45].

    Article Title: RUBAT Studio: A Unified Workbench for Multichannel Bioacoustic Data Acquisition
    Article Snippet: RUBAT Studio v4.0 was packaged using the MATLAB Application Compiler to produce standalone executables requiring only the freely distributable MATLAB Runtime.

    Article Title: Autophagy dysfunction in iPSCs-derived neurons and midbrain organoids carrying a SNCA triplication.
    Article Snippet: Neural stat compiler files were used for data analysis in MATLAB.

    Article Title: Predicting Cell Adhesion States on Nanopillar Arrays with a Nano‐Bio Interface Model: From Modeling to Functional Device Design
    Article Snippet: Nanopillar arrays (NAs) are widely employed as versatile nanostructures for biological applications.. Cells on NAs adopt three adhesion states—“top”, “middle”, and “bottom”—each corresponding to distinct biological functions.. Although these adhesion states are influenced by NAs geometry, existing models overlook the role of the membrane reservoir—an intrinsic cellular property—in regulating membrane tension during cell settling, resulting in an incomplete mechanistic understanding and limited predictive capability.

    Article Title: An Integrated Framework for Automated Image Segmentation and Personalized Wall Stress Estimation of Abdominal Aortic Aneurysms
    Article Snippet: The script can be compiled into a standalone executable (e.g., via MATLAB Compiler) that runs with the free MATLAB Runtime, so end users do not require a MATLAB license [ ].

    Generated:

    Article Title: WAH- i : Optimising Microphone Array Geometry for Customised Localisation Accuracy
    Article Snippet: .. To support deployment beyond a MATLAB development environment, standalone executables were generated using the MATLAB Compiler ( ). ..



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    Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Multimodal setup in MEG environment. In the pictures, the black cables with fibre optics based sensors attached on the body and head are optical fibres for measurements of cNIBP and NIRS. On the right, shown is performing of simultaneous recording with the setup. During imaging, the display is used to instruct the subject to perform the given task.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Imaging

    Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Comparison of mean power values (black dots, whiskers = SD) measured with magnetometers ( a ) and planar gradiometers ( b and c ), with (x axis) and without (y axis) the multimodal setup. For better visualisation the plots show an extract of all data, which were shown in each inset separately. In all cases the data can be well explained by a linear fit (red line). Note the slight positive intercept of the linear fits due to smaller power values when the multimodal setup is applied. The external sensors for NIRS are attached on back of the head and on forehead above left eye. Sensors for cNIBP are attached on chest and neck (see Figure ).

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Comparison

    Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Journal: Scientific Reports

    Article Title: Multimodal brain imaging with magnetoencephalography: A method for measuring blood pressure and cardiorespiratory oscillations

    doi: 10.1038/s41598-017-00293-7

    Figure Lengend Snippet: Averaged responses for PTT ( a ), BP ( b ), HR ( c ) measured with the cNIBP device; HbO/Hb ( d ) measured with the NIRS device from back of the head and four scouts (MEG) covering visual (green line), auditory (brown line), motor (dark yellow line) and temporal pole (blue line) brain areas ( e ). Average for NIRS and cNIBP data was calculated using values obtained during 4 breath holding sequences. Vertical bars represent standard deviation of the values. In addition, ( f ) shows an averaged response of 8 breath holds using the same breath hold task but recorded independently with our MREG multimodal setup . In all subfigures t = 0 marks the beginning of breath holding for 30 s, highlighted with grey area.

    Article Snippet: Measured raw NIRS time courses were converted into two time courses representing temporal changes in HbO and Hb concentrations using Matlab-based NIRS data analysis tool HoMer2.

    Techniques: Standard Deviation