Review



classification learner package in  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 90

    Structured Review

    MathWorks Inc classification learner package in
    Classification Learner Package In, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/pm31591693-66-9-16
    Average 90 stars, based on 1 article reviews
    classification learner package in - by Bioz Stars, 2026-09
    90/100 stars

    Images

    Related Articles

    other:

    Article Title: Flexible multichannel muscle impedance sensors for collaborative human-machine interfaces
    Article Snippet: The impedance measurement hardware transmitted the impedance patterns to a host computer, where a machine learning algorithm (coded in MATLAB) predicted human gestures and muscle force from the impedance patterns.

    Article Title: Combining array-assisted SERS microfluidic chips and machine learning algorithms for clinical leukemia phenotyping.
    Article Snippet: The disease progression and treatment options of leukemia between different subtypes vary considerably, emphasizing the importance of phenotyping.. However, early typing of leukemia remains challenging due to the lack of highly sensitive and specific analytical tools.. Herein, we propose a SERS-based platform for the classification of acute lymphoblastic T-cell leukemia (T-ALL) and chronic myeloid leukemia (CML) through the combination of machine learning and microfluidic chips.

    Article Title: Rapid identification of marine microplastics by laser-induced fluorescence technique based on PCA combined with SVM and KNN algorithm.
    Article Snippet: The laser-induced fluorescence technique has the advantage of fast and non-destructive detection and can be used to classify types of marine microplastics.. However, spectral overlap poses a challenge for qualitative and quantitative analysis by conventional fluorescence spectroscopy.. In this paper, a 405 nm excitation laser source was used to irradiate 4 types of microplastic samples with different concentrations, and a total of 1600 sets of fluorescence spectral data were obtained.

    Article Title: Flexible multichannel muscle impedance sensors for collaborative human-machine interfaces
    Article Snippet: The motions of the virtual knife, hand, and patient skin were updated in real time based on the predicted human motions using a machine learning algorithm implemented in MATLAB.

    Article Title: Optimal placement of distributed generation in power distribution system and evaluating the losses and voltage using machine learning algorithms
    Article Snippet: The assessment of the cascaded machine learning algorithm’s performance is conducted using MATLAB software, comparing it with existing algorithms.

    Article Title: Unraveling Metabolic Changes following Stroke: Insights from a Urinary Metabolomics Analysis
    Article Snippet: VIAVC is a machine learning algorithm implemented in MATLAB that identifies important metabolites in a dataset by using binary matrix resampling (BMR) to generate subsets of variables with equal probability [ ].

    Article Title: Abstracts from the 30th Meeting of the Dysphagia Research Society.
    Article Snippet: s from the 30th Meeting of the Dysphagia Research Society The Author(s), under exclusive licence to Springer Science?Business Media, LLC, part of Springer Nature 2024 Held virtually due to the COVID-19 Pandemic.. March 15–17, 2022.. Sponsorship: Publication of this supplement was funded by the Dysphagia Research Society.

    Article Title: Asian Pacific Digestive Week (APDW) 2024, 21-24 NOVEMBER 2024 | Bali Nusa Dua Convention Centre.
    Article Snippet: Oral Presentation 1, APDW Theatre 1, Exhibition Hall, November 22, 2024, 10:30 AM 11:50 AM Objective: This study evaluates the diagnostic capabilities of a new tool, Stent Pusherguided Endobiliary Forceps (SPECS) in assessing indeterminate biliary strictures.. Procedure (Material): SPECS procedure utilises a 10F sized stent pusher, advanced over a guidewire.. Once pusher is correctly positioned with confirmation by fluoroscopy, contrast is injected via the pusher to redelineate the stricture followed by biopsies that are performed using a paediatric biopsy forceps.



    Similar Products

    90
    MathWorks Inc classification-learner package
    Characteristics, classification and objectives of the machine learning models used in the studies
    Classification Learner Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/pmc11843972-61-27-27
    Average 90 stars, based on 1 article reviews
    classification-learner package - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    MathWorks Inc 2018 software package classification learner
    Characteristics, classification and objectives of the machine learning models used in the studies
    2018 Software Package Classification Learner, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/10__1016_slash_j__optcom__2024__131238-134-2-1
    Average 90 stars, based on 1 article reviews
    2018 software package classification learner - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    MathWorks Inc classification learner package
    Characteristics, classification and objectives of the machine learning models used in the studies
    Classification Learner Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/pm36129797-3001-1-1
    Average 90 stars, based on 1 article reviews
    classification learner package - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    MathWorks Inc classification learner package in
    Characteristics, classification and objectives of the machine learning models used in the studies
    Classification Learner Package In, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/pm31591693-66-9-16
    Average 90 stars, based on 1 article reviews
    classification learner package in - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    MathWorks Inc classification learner packages
    Characteristics, classification and objectives of the machine learning models used in the studies
    Classification Learner Packages, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification-learner+package/pmc05394550-288-8-12
    Average 90 stars, based on 1 article reviews
    classification learner packages - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    Image Search Results


    Characteristics, classification and objectives of the machine learning models used in the studies

    Journal: BMC Medical Research Methodology

    Article Title: Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review

    doi: 10.1186/s12874-025-02463-y

    Figure Lengend Snippet: Characteristics, classification and objectives of the machine learning models used in the studies

    Article Snippet: Varghese [ ] b , Incidence risk stratification (classification): QSVM (radiomics-based) , Risk stratification for prostate cancer in low- and high-risk patients , desktop-based , CDSS , MATLAB's Classification-Learner Package , NR , NR.

    Techniques: Software, Biomarker Discovery, Diagnostic Assay, Imaging, Staining