Search Results - Lawlor, A.
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Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis
Leckey, C., van Dyk, N., Doherty, C., Lawlor, A., Delahunt, E.Published in British Journal of Sports Medicine (2025)article“…Lawlor, A.…”
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Using pseudo cases and stratified case-based reasoning to generate and evaluate training adjustments for marathon runners
Feely, C., Caulfield, B., Lawlor, A., Smyth, B.Published in Artificial Intelligence XLI (2024)article“…Lawlor, A.…”
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Mining marathon training data to generate useful user profiles
Berndsen, J., Smyth, B., Lawlor, A.Published in Machine Learning and Data Mining for Sports Analytics (2020)article“…Lawlor, A.…”
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Using case-based reasoning to predict marathon performance and recommend tailored training plans
Feely, C., Caulfield, B., Lawlor, A., Smyth, B.Published in Case-Based Reasoning Research and Development. ICCBR 2020 (2020)article“…Lawlor, A.…”
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An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression
Doherty, C., Keogh, A., Davenport, J., Lawlor, A., Smyth, B., Caulfield, B.Published in Journal of Science and Medicine in Sport (2020)article“…Lawlor, A.…”
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Prediction equations for marathon performance: A systematic review
Keogh, A., Smyth, B., Caulfield, B., Lawlor, A., Berndsen, J., Doherty, J.Published in International Journal of Sports Physiology and Performance (2019)article“…Lawlor, A.…”