Sports institute, Jilin Normal University, Siping, Jilin 136000, China.
Comput Intell Neurosci. 2022 Jul 30;2022:9687496. doi: 10.1155/2022/9687496. eCollection 2022.
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.
机器学习是一门跨学科的研究，旨在使计算机程序能够像人类学习一样进行操作，其技术在医学领域得到了广泛的应用。本文旨在研究如何利用基于机器学习的智能医学来分析和研究运动员的体质和健康状况，并描述机器学习算法。本文提出了基于机器学习的智能医疗诊断问题，然后详细阐述了机器学习的概念和相关算法，并设计和分析了一个运动员体质监测和健康状况评估系统的案例。实验结果表明，运动员的体能监测和健康状况评估系统能够满足用户的需求。基于 LSTM 方法的文本分类效果略逊于 SVM 效果，其中糖尿病的召回率不超过 40%，使用模糊匹配后，脑梗死的召回率提高了 26.5%。
