The sternalis muscle was highly prevalent in normal Chinese adults. MDCT is an effective method to demonstrate this muscle in vivo.

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.

With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5° and the highest temperature was 37.1° under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed in this paper is effective and feasible.

Nowadays, the remediation of agricultural soils polluted by Cd and Pb is urgently required. In this study, we used the palygorskite (PAL) as a carrier for nanoscale zero-valent iron (nZVI) to synthesize a new type of stabilizer (PAL-nZVI). After 45 days of incubation, the soil pH increased by 1.80 pH units.The batch experiments exhibited that the bioavailability and leaching toxicity decreased significantly (P < 0.05) with the addition of PAL-nZVI. The data concluded that the 30 days was a critical period for Cd and Pb stabilization and the optimum dosage of PAL-nZVI was 6%. Moreover, the application of PAL-nZVI could transform the speciation of Cd and Pb from labile fraction to stable fraction (the maximum residual percentage of Cd and Pb increased by 27.34% and 36.57%, respectively) after 30 days of incubation. The pot experiments indicated that the application of PAL-nZVI could enhance the growth of corn (Zea mays L.), reduce the accumulation of heavy metals from the soil and decrease the phytotoxicity of Cd and Pb in the soil. These results suggested that the PAL-nZVI, which is high-efficiency and low-cost, can be a feasible stabilizer for the soils contaminated by Cd and Pb.

No abstract