Classification of sodium MRI data of cartilage using machine learning

DOI
10.1002/mrm.25515
Madelin G.; Poidevin F.; Makrymallis A.; Regatte R. R.
Bibliographical reference

Magnetic Resonance in Medicine Volume 74, Issue 5, pages 1435–1448, November 2015

Advertised on:
11
2015
Number of authors
4
IAC number of authors
1
Refereed citations
0
Description
To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: support vector machine, k-nearest neighbors, naïve Bayes, discriminant analysis, linear regression, logistic regression, neural networks, decision tree, and tree bagging were tested.
Type
Refereed

It may interest you

  • Refereed
    Atmospheric Parameters and Abundances of Cool Red Giant Stars
    Understanding the atmospheric parameters of stars on the top of the RGB is essential to reveal the chemical composition of the Milky Way, as they can be used to probe the farthest parts of our Galaxy. Our goal is to determine the chemical composition of 21 RGB stars with T eff < 4200 K selected from the APOGEE-2 DR17 database using new observations
    Dencs, Z. et al.

    Advertised on:

    5
    2024
    Bibcode
    2024PASP..136e4202D
    Citations
    0
  • Refereed
    The GALAH survey: tracing the Milky Way's formation and evolution through RR Lyrae stars
    Stellar mergers and accretion events have been crucial in shaping the evolution of the Milky Way (MW). These events have been dynamically identified and chemically characterized using red giants and main-sequence stars. RR Lyrae (RRL) variables can play a crucial role in tracing the early formation of the MW since they are ubiquitous, old (t ≥ 10
    D'Orazi, Valentina et al.

    Advertised on:

    6
    2024
    Bibcode
    2024MNRAS.531..137D
    Citations
    0
  • Refereed
    The Gaia-ESO Survey: Calibrating the lithium-age relation with open clusters and associations. II. Expanded cluster sample and final membership selection
    Context. The Li abundance observed in pre-main sequence and main sequence late-type stars is strongly age-dependent, but also shows a complex pattern depending on several parameters, such as rotation, chromospheric activity, and metallicity. The best way to calibrate these effects, and with the aim of studying Li as an age indicator for FGK stars
    Gutiérrez Albarrán, M. L. et al.

    Advertised on:

    5
    2024
    Bibcode
    2024A&A...685A..83G
    Citations
    0