| Abstract: |
With the rapid development of medical informatization, the existing hospital information system and electronic health record system can no longer meet the demand for storing and processing massive medical data, analyzing and mining, and diversified medical data services. After the generation and collection of massive medical data, how to effectively store heterogeneous, massive, real-time, and diverse data to meet the rapid and precise response to complex medical data is an urgent problem to be solved. How to utilize data mining technology to deeply analyze the massive medical big data and provide valuable medical big data services for patients, so as to realize "preventing diseases before they occur", is an important problem in the current medical research. This article analyzed the medical data large-scale processing technology based on the March algorithm and explored its application and advantages in the medical field. The March algorithm is an efficient algorithm for processing large-scale data, which can effectively improve data processing speed and efficiency by dividing the data into small blocks for parallel processing. The experimental results indicated that as the number of files increased from 10000 to 50000, the memory usage of the March algorithm was relatively low within the same range, increasing from 0.68 to 13.26. [ABSTRACT FROM AUTHOR] |