Search Results - Äyrämö, S.

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  1. 1

    Global positioning system-derived metrics and machine learning models for injury prediction in professional rugby union players

    Ren, X., Boisbluche, S., Philippe, K., Demy, M., Äyrämö, S., Rautiainen, I., Ding, S., Prioux, J.
    Published in European Journal of Sport Science (2025)
    “…Äyrämö, S.…”
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  2. 2

    Machine learning in rugby union: predicting and identifying key performance indicators for professional rugby union players in match play based workload

    Ren, X., Boisbluche, S., Philippe, K., Demy, M., Äyrämö, S., Rautiainen, I., Ding, S., Prioux, J.
    Published in European Journal of Sport Science (2025)
    “…Äyrämö, S.…”
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  3. 3

    Quantification of workload and characterisation of key performance factors in elite adolescent female volleyball players using machine learning

    Bouzigues, T., Candau, R., Äyrämö, S., Maurelli, O., Prioux, J. “…Äyrämö, S.…”
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  4. 4

    Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity

    Girka, A., Kulmala, J.-P., Äyrämö, S. “…Äyrämö, S.…”
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  5. 5

    Talent identification in soccer using a one-class support vector machine

    Jauhiainen, S., Äyrämö, S., Forsman, H., Kauppi, J.-P. “…Äyrämö, S.…”
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  6. 6

    Prediction of active peak force using a multilayer perceptron

    Niemelä, M., Kulmala, J. P., Kauppi, J. P., Kosonen, J., Äyrämö, S.
    Published in Sports Engineering (2017)
    “…Äyrämö, S.…”
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