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

Aug 5, 2026

Upload by Logic

The study investigates correlations between the cytokine and adipokine Tumour Necrosis Factor Alpha (TNF-α) and body composition and lipid metabolism parameters in young high-level athletes following an incremental treadmill test. A five-participant sample limits univariate statistical findings when multiple biomarkers and time points are considered, motivating exploratory machine learning for a more holistic analysis. Results show a negative association between TNF and HDL and a similarity between TNF and LDL, without establishing causality. Findings suggest possible immune and lipid modulation induced by exercise, requiring further investigation.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages8

Reading Time20 min

AccessFree to download

Abstract

Introduction

Materials and Methods

Participants

Experimental design

Statistical analysis

Original Article Machine learning in sports medicine: A new approach in human exercise ANDREA SCHULZ GALVÃO1, MARCELLE KARYELLE MONTALVÃO GOMES1, NAIRANA CRISTINA SANTOS FREITAS1, LEONARDO SANTOS MACEDO1, DANIEL MANCINI OLIVEIRA1, MÁRCIO VINICIUS ABREU VERLI1, ROBERTO LOHN NAHON2, LUIS CARLOS OLIVEIRA GONÇALVES 1,3, ANÍBAL MONTEIRO MAGALHÃES-NETO1,3 1 Graduate Program in Physical Education (PPGEF). Federal University of Mato Grosso (UFMT). Brazil 2 Brazilian Society of Orthopedics (SBOT). Brazilian Society of Exercise and Sports Medicine (SBME). Brazil 3 Graduate Program in Basic and Applied Immunology and Parasitology (PPGIP). Federal University of Mato Grosso (UFMT). Brazil ABSTRACT 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. Keywords: Sport medicine; Data mining; Immunometabolism; Sportomics. Cite this article as: 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, in press. [https://doi.org/10.14198/jhse.2023.182.19](https://doi.org/10.14198/jhse.2023.182.19) 1 Corresponding author. Graduate Program in Physical Education (PPGEF). Federal University of Mato Grosso (UFMT) . Brazil. [https://orcid.org/0000-0001-5368-1194](https://orcid.org/0000-0001-5368-1194) E-mail: [luisogoncalves@yahoo.com.br](luisogoncalves@yahoo.com.br) [Submitted for publication December 23](Submitted for publication December 23), 2022. Accepted for publication January 30, 2023. Published in press February 10, 2023. JOURNAL OF HUMAN SPORT & EXERCISE ISSN 1988-5202. © Faculty of Education. University of Alicante. doi:10.14198/jhse.2023.182.19 INTRODUCTION Advances in technology involving processing, memory, storage, and richness of data, with the rapid dissemination of information over the internet and the formation of large databases, have generated machine learning strategies in different areas, from games such as Poker to video games, marketing, administration and in recent years reaching the field of medical and health sciences (Deo, 2015) . This knowledge quickly reached the field of sports medicine, with contributions in the field of genomics, sportomics, biomechanics, kinesiology, sports training and performance, among others (Cust et al., 2019; Tanisawa et al., 2020; Antink et al. , 2021; Gonçalves et al., 2022) . From a multivariate statistical strategy with machine learning, the study's primary objective was to investigate possible relationships between the Tumour Necrosis factor and lipid profile in young running athletes. MATERIALS AND METHODS This cross-sectional, descriptive, and observational study was based on a sports strategy with high-level young athletes. Participants The studied population comprises high-level track and field athletes, male, from the city of Barra do

FAQs

What was the main aim of the study?

To investigate possible relationships between TNF-α and parameters of body composition and lipid metabolism in young, high-level athletes after an incremental treadmill test.

How was exercise testing performed?

Athletes performed warm-up stretching, followed by a progressively increased treadmill protocol until exhaustion, with cardiovascular monitoring via an exercise electrocardiogram and metabolic assessment using a computerized gas analyser with a face mask.

What key associations were found between TNF-α and lipid markers?

TNF-α showed a negative correlation with HDL and a similarity between TNF-α and LDL, while the results do not support a cause-and-effect conclusion.

Aug 5, 2026

Upload by Logic