Assessment of Physical Fitness and Health Status of Athletes Based on Intelligent Medical Treatment under Machine Learning.

Abstract

Machine learning is an interdisciplinary study of how to make computer programs perform similar to human learning, and its techniques are widely used in the medical industry. The purpose of this paper is to study how to use machine learning-based intelligent medicine to analyze and study the assessment of athletes' physique and health status and describe the machine learning algorithm. This paper puts forward the problem of intelligent medical diagnosis, which is based on machine learning, and then elaborates on the concept of machine learning and related algorithms, and designs and analyzes a case of an athlete's physique monitoring and health status assessment system. The experimental results show that the athlete's physical fitness monitoring and health status evaluation system can meet the needs of users. The text classification effect based on the LSTM method is slightly inferior to the SVM effect, in which the recall rate of diabetes is not more than 40%, and the recall rate of cerebral infarction is improved by 26.5% after using fuzzy matching.