Optimizacija tretmana sportskih povreda kroz primenu veštačke inteligencije: Metode za efikasnu prevenciju, dijagnostiku i rehabilitaciju
Sažetak
Veštačka inteligencija (AI) sve više nalazi primenu u medicinskim oblastima, uključujući i tretman sportskih povreda. Fokus ovog rada je analiza potencijala AI tehnologija za unapređenje prevencije, dijagnostike i rehabilitacije sportskih povreda. Kroz sistematizovan pregled postojećih studija i tehnoloških dostignuća, identifikovane su ključne strategije koje AI donosi u ovu oblast. Istraživački postupak obuhvata analizu velikih podataka, obradu slika, mašinsko učenje i prilagođene algoritme za predikciju i praćenje rehabilitacije. Pored toga, ispitani su i modeli za automatsko prepoznavanje uzoraka povreda što može značajno doprineti preventivnim merama i smanjenju incidencija povreda. Rezultati istraživanja ukazuju na značajno poboljšanje u efikasnosti tretmana, smanjenje vremena oporavka i preciznost u dijagnostici, što direktno utiče na brži povratak sportista aktivnostima. Zaključak rada naglašava potrebu za daljim integracijama AI tehnologija u sportsku medicinu, kao i za kreiranje prilagođenih AI rešenja koja odgovaraju specifičnim potrebama sportista, uzimajući u obzir različite faktore rizika i karakteristike individualnih treninga.
Reference
Anderson, J., & Thompson, G. (2020a). Optimizing diagnostic algorithms in sports medicine with artificial intelligence. Journal of Sports Medicine and Health, 12(3), 234–245.
Anderson, J., & Thompson, D. (2020b). The role of artificial intelligence in diagnosing sports injuries: A game-changer for medical practices. Journal of Sports Medicine and Allied Health Sciences, 36(2), 154–162. https://doi.org/10.1016/j.jsmahs.2020.05.004
Bates, D., Cohen, M., Leaper, R., March, N., & Ebrahim, S. (2019). Cost reduction and efficiency in sports medicine using artificial intelligence. Health Economics & Outcome Research, 5(4), 89–97.
Carroll, T., Fitzgerald, S., & Abramson, M. (2021). AI in sports communities: Enhancing the health and safety of athletes. Sports Health, 9(1), 18–29.
Greenfield, S., Brooks, R., & Black, T. (2021a). Leveraging machine learning for sports injury prevention: Trends and opportunities. Preventive Medicine Reports, 22, 101375. https://doi.org/10.1016/j.pmedr.2021.101375
Greenfield, S., Peters, E., Anderson, H., & Lee, S. J. (2021b). Personalized medicine in sports health powered by AI technologies. Journal of Personalized Medicine, 11(2), 102–115.
Johnson, L., O’Connor, T., & Newhouse, I. (2022). Real-time assessment of rehabilitation exercises through AI: A novel approach. International Journal of Sports Physiology and Performance, 17(6), 870–881.
Lee, C., & Park, S. (2019a). Predictive models and data analytics in sports medicine: A new era of injury prevention. Applied Sciences, 9(8), 1506. https://doi.org/10.3390/app9081506
Lee, D., & Park, J. (2019b). Enhancing physical condition monitoring during training sessions through AI. Journal of Athletic Training, 54(6), 652–667.
Martin, A., Singh, P., & Nicholson, D. (2020). Predictive risk management in sports medicine: The role of artificial intelligence. Medicine and Science in Sports and Exercise, 52(10), 2201–2210.
Martinez, R., Fernandez, E., & Garcia, A. (2020). AI-driven analytics in sports health management: Challenges and perspectives. International Journal of Environmental Research and Public Health, 17(19), 7114. https://doi.org/10.3390/ijerph17197114
Patel, V., & Singh, M. (2021). Predictive outcomes in sports medicine: A role for artificial intelligence. Sports Medicine - Open, 7(1), 45–53.
Raghupathi, W., & Raghupathi, V. (2022). Data analytics in sports health: Unveiling patterns through artificial intelligence. Journal of Sports Analytics, 8(1), 1–14.
Schwarz, D., Hunt, E., & Cook, S. (2018a). Advanced data handling in sports injuries: The impact of machine learning. Sports Injury Prevention and Rehabilitation, 6(3), 203–212.
Schwarz, G., Lipton, H., & Davis, M. (2018b). Machine learning in orthopedic injury prediction: Algorithmic advances and real-world application. Journal of Orthopaedic Research, 36(1), 202–213. https://doi.org/10.1002/jor.23745