K-Means聚类算法在医学专业课程成绩分析中的应用  

Application of K-Means Clustering Algorithm in the Analysisof Medical Professional Course Results

作　　者：杨雨悦 赵永峰 徐三研 盛婧怡 雷娟 甘卫华 宋佳宇[1,2] Yang Yuyue;Zhao Yongfeng;Xu Sanyan;Sheng Jingyi;Lei Juan;Gan Weihua;Song Jiayu(School of Pediatrics,Nanjing Medical University,Nanjing 210000,China;The Second Affiliated Hospital of Nanjing Medical University,Nanjing 210000,China)

机构地区：[1]南京医科大学儿科学院,南京210000 [2]南京医科大学第二附属医院,南京210000

出　　处：《黑龙江科学》2025年第7期36-39,共4页Heilongjiang Science

基　　金：南京医科大学儿科学院教育研究课题“后疫情时代‘互联网+’混合式教学在儿科中的应用”(2022eK18)。

摘　　要：对医学专业课程成绩进行数据挖掘,为提升教学质量提供参考。利用K-means聚类算法,对南京医科大学医学专业(内科学与儿科学)学生的成绩进行分析。结果表明,学生原始成绩近似成正态分布,运用手肘法及轮廓系数法得到适合医学专业学生课程成绩分析的模型。对医学生的课程成绩进行聚类分析与评价,有益于实施优质化且针对性的教学方案,提升医学生的学业成绩。The study mines the results of medical professional courses to provide reference for improving teaching quality,analyzes the results of medical majors(Internal Medicine and Pediatrics)in Nanjing Medical University through K-means clustering algorithm.The results show that the students’original grades are approximately normal distribution,and a model suitable for the analysis of medical students’grades is obtained with elbow method and contour coefficient method.The clustering analysis and evaluation of medical students’course performance is beneficial to the implementation of high-quality and targeted teaching programs,and the improvement of medical students’academic performance.

关 键 词：K-MEANS聚类算法 内科学 儿科学 成绩分析模型 

分 类 号：G642[文化科学—高等教育学] R-4[文化科学—教育学]