Machine learning in sports medicine

A new approach in human exercise




Sport medicine, Data mining, Immunometabolism, Sportomics


The present study aimed to investigate the possible correlations between the cytokine and adipokine Tumour Necrosis Factor Alpha with parameters of body composition and lipid metabolism in young, high-level athletes after an incremental treadmill test observed in a sample of five individuals, male, high-level running athletes who the difficulty of treating large databases with different individuals, multiple biomarkers, and collection times, in addition to physical parameters and sample characteristics, added to the decrease in new findings induced by the application of statistical tools of univariate analysis, indicate the need to apply exploratory machine learning strategies, generating holistic and integrated analysis of the results. The present study showed a negative correlation between TNF and HDL and a similarity between the same TNF and LDL. These findings do not indicate a cause-and-effect relationship but suggest a possible modulation of the immune system, lipid metabolism, and exercise that requires further investigation.


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Machine learning in sports medicine: A new approach in human exercise


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How to Cite

Galvão, A. S., Gomes, M. K. M., Freitas, N. C. S., Macedo, L. S., Oliveira, D. M., Verli, M. V. A., Nahon, R. L., Gonçalves, L. C. O., & Magalhães-Neto, A. M. (2023). Machine learning in sports medicine: A new approach in human exercise. Journal of Human Sport and Exercise, 18(2), 501–508.



Sport Medicine, Nutrition & Health