Construction of intelligent supervision platform for college students’ physical health for intelligent medical service decision-making - Guo, Fei (Frontiers in Physics, 2023)
Due to the rapid changes in current technology, machine learning and high-performance computing in medical applications also usher in new development opportunities. They are widely used in medical data analysis, diagnostic decision-making, disease prediction, disease assisted diagnosis, disease prognosis evaluation, new drug research and development, health management, and other fields. The impact of medical application on daily life is also increasing, which makes the use of intelligent medical service decision-making more extensive. However, with the continuous improvement and development of the population's physical fitness, the physical fitness of university students is deteriorating. Physical decline has become a common concern. Therefore, it is of great significance to investigate the physical condition of college students and find a more suitable method to promote the physical health of college students. It helps college students better engage in learning and life, enabling them to adapt to work faster and better meet the current social development needs for college students' physical fitness. For this reason, this paper proposes the idea of building a smart supervision platform for college students' physical health through smart medical service decision-making. Through empirical research on this platform, it is found that the method of building the platform proposed in this paper is more conducive to the improvement of college students' physical health. The excellent grade of freshmen in this platform is 5.4% higher than that of the traditional platform, and the excellent grade of sophomores in the test is 6.31% higher than that of the traditional platform, the excellent grade of college students' physical health test on this platform accounts for a higher proportion. The platform provides corresponding personalized sports programs through real-time monitoring of students' physical health, so as to realize teaching students in accordance with their aptitude, scientifically guide students' physical exercise, and accurately improve students' physical health. Meanwhile, research on the use of big data in sports has also led to advances in machine learning and high performance computing for medical applications, which improves their shortcomings.