Leveraging explainable machine learning to identify gait biomechanical parameters associated with anterior cruciate ligament injury

HIGHLIGHTS

• who: Christos Kokkotis from the InstitutUniversity of have published the paper: Leveraging explainable machine learning to identify gait biomechanical parameters associated with anterior cruciate ligament injury, in the Journal: Scientific Reports Scientific Reports
• what: Having selected the most accurate ML model, this study attempted to uncover the rationale behind the decision-making mechanism of the trained model and therefore provide an alternative and a more holistic approach of quantifying the contribution of the input biomechanical parameters in the classification process.
• how: Kinematic data were collected using 10 optoelectronic | 126647 | 7 Vol.(0123456789) Data . . .
  

   

  

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