External validation of a machine learning-based web application for personalized testing of objective functioning using the five-repetition sit-to-stand test - Takeaways - MDSpire
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Validation of a Machine Learning-Driven Web Tool for Customized Assessment of Objective Functioning via the Five-Repetition Sit-to-Stand Test

  • By

  • Kenneth Arockia

  • Massimo Bottini

  • Anita M. Klukowska

  • Victor Gabriel El-Hajj

  • Maria Gharios

  • Ali Buwaider

  • Carlo Serra

  • Luca Regli

  • Marc L. Schröder

  • Victor E. Staartjes

  • August 18, 2026

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  • 1

    The five-repetition sit-to-stand (5R-STS) test is used to assess objective functional impairment in patients with degenerative lumbar spine disease.

  • 2

    A personalized machine learning model was developed to improve the accuracy of functional impairment classification by incorporating demographic variables.

  • 3

    External validation of the machine learning model was conducted on a diverse cohort of healthy individuals from multiple countries.

  • 4

    The study emphasized the importance of external validation to confirm the model's predictive capabilities and adaptability across different demographics.

  • 5

    Participants' 5R-STS test times were compared against personalized upper limits of normal derived from demographic data to classify functional impairment.

Original Source(s)

External validation of a machine learning-based web application for personalized testing of objective functioning using the five-repetition sit-to-stand test

  • by Kenneth Arockia, Massimo Bottini, Anita M. Klukowska, Victor Gabriel El-Hajj, Maria Gharios, Ali Buwaider, Carlo Serra, Luca Regli, Marc L. Schröder, Victor E. Staartjes

  • August 18, 2026

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