The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine
DOI:
https://doi.org/10.12775/QS.2025.41.60392Keywords
Artificial intelligence, machine learning, Imaging Diagnostics, Sports Medicine, Injury Prevention, Predictive Analytics, Healthcare Technology, Computer Vision, Deep LearningAbstract
This review paper examines the burgeoning role of Artificial Intelligence (AI) in medicine, particularly in diagnostics and sports medicine, by enhancing accuracy, efficiency, and personalization in patient care. With 25 years of development, AI technologies, including machine learning, deep learning, natural language processing, and computer vision, are making significant strides in interpreting medical data and supporting clinical decision-making. Recent advancements allow AI systems to analyze physiological, biomechanical, and behavioral data, leading to improved injury prevention and performance optimization in athletes. These AI-driven tools can predict injury risks by evaluating training loads, biomechanics, and real-time physiological signals. However, their integration into healthcare raises critical ethical concerns related to data privacy, algorithmic bias, and transparency. Ensuring responsible AI use requires adherence to established medical ethics principles—autonomy, beneficence, nonmaleficence, and justice. As AI continues to reshape healthcare delivery, it is essential to strike a balance between technology and compassionate care. By focusing on ethical considerations and refining AI technologies, the healthcare community can harness AI's full potential while safeguarding patient interests and enhancing outcomes. This transformative journey signifies not just technological advancement, but a commitment to improving human health through informed, ethical practices. The future of AI in medicine hinges on maintaining this delicate equilibrium, ensuring that innovations augment rather than diminish the core values of patient-centric care.
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Copyright (c) 2025 Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda
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