Objective:To understand the topics, hotspots and trends of researches in the field of infodemiology.Methods:Based on Web of Science Core Collection, the literatures related to infodemiology were collected until March 3rd, 2023. With VOSviewer version 1.6.19, published features including numbers of annual published articles, journal, organization and author information were analyzed. Based on the top 100 keywords in frequency, cluster analysis was used to analyze the research hotspots and trends.Results:Until March 3rd, 2023, a total of 14 521 articles were retrieved. The annual number of published articles exceeded 100 in 2001 and showed an increasing trend in following years. In 2020, the number increased doubly due to the COVID-19, and reached the peak in 2021 (2 593 articles) and declined in 2022 (1 973 articles). The top 10 journals in publication number came from 5 countries, with a total of 2 099 articles (14.46%, 2 099/14 521). The top 10 research institutions (excluding World Health Organization) came from 4 countries, with a total of 2 943 articles (20.27%, 2 943/14 521). The top 10 authors publishing over 40 articles per person were from China and Britain, with a total of 566 articles (3.90%, 566/14 521). According to high frequency keywords, 4 key research fields including HIV/AIDS, epidemiology, epidemic and COVID-19, and the 3 hotspots including HIV/AIDS public health monitoring, epidemiology monitoring and COVID-19 information epidemic were clustered.Conclusions:The current hotspot of infodemiology focuses on the infodemic management of COVID-19 including SARS-CoV-2, infodemiology, mental health and social media. In the future, the research will focus on the public health and carry out epidemiological research in the way of information epidemic management.

The incidence of multiple pregnancies has increased worldwide due to the use of assisted reproductive technologies, such as in vitro fertilization. In the USA, the rate of twin births has increased by nearly 80

The outbreak of novel coronavirus pneumonia(COVID-19)endangers the whole world，seriously endangers people’s lives and health， and affects social and economic development.The SIR model is a typical dynamic model of infectious diseases.This paper selects th

目的:评价新冠肺炎疫情下浙江某医学院校学生对网络课程的学习认同感.方法:以浙江某医学院233名学生为调查对象,对学校网络课程分别运用六维学习认同感量表进行调查,采用方差分析和多元线性回归方法统计分析.结果:方差分析结果表明网络学习认同感问卷量表各维度在不同特征项目间差异有统计学意义(P＜0.05);多元线性回归显示医学生网络学习认同感与部分特征项目间呈正相关.结论:提高网络课程学习认同感有助于促进医学生学习兴趣,从而有助于提高医学生学业水平.

本文回顾了中美合作卫生信息管理专业专科层次教育项目的建设与管理过程,分析了生源质量、学生出国意愿、外籍教师选拔及派遣、教育教学质量监督与评估等方面存在的问题,对于高等专科医学类中外合作办学、外籍教师规范管理、保证并提升中外合作高等教育项目的教学质量提出了建设性意见建议.

以浙江某医学院校临床专业和非临床相关专业共680名在校生为调查研究对象,运用六维职业认同感问卷进行调查,采用方差分析和多元线性回归方法进行统计分析.方差分析结果表明,职业认同感问卷各维度得分在不同个体特征之间差异有统计学意义(P＜0.01);多元线性回归结果显示,职业认同感与部分个体特征间具有负相关,职业认同感受不同年级、高考志愿等个体特征影响.

In this study, an Ant Colony Optimization (ACO) clustering approach is proposed for medical diagnosis to assign patients into different primary headache groups with Visual C++ program. By experiments, 375 patients were classified into Migraine, Tension-Type Headache (TTH) and Trigeminal Autonomic Cephalalgias (TACs). Results show that the clustering algorithm with ant colony can be important supportive for the medical experts in diagnostic.

BACKGROUND:In recent years, the use of the fuzzy c-means (FCM) clustering techniques in medical diagnosis has steadily increased, because of its effectiveness in recognizing systems in the medical database to help medical experts diagnosing diseases. However, its performance is highly dependent on the randomly initialized cluster centroids which may allow the diagnosis to be trapped into the problem of the local optimum.OBJECTIVE:This paper proposes a multiple fuzzy c-means (MFCM) algorithm for medical diagnosis.METHODS:The new method optimizes the initial optimizing cluster centers by comparing the Euclidean distance between patient data. Further, this paper assigns a set of weights to the features of a certain disease to equalize their difference influence as a substitute for data normalization.RESULTS:The performance of proposed MFCM algorithm was demonstrated through dividing complex primary headache data into Migraine, Tension-Type Headache (TTH), Trigeminal Autonomic Cephalalgias (TACs) and other primary headache disorders. In addition the superiority of MFCM algorithm was proven by comparing analytical results with other state-of-the-art clustering methods.CONCLUSIONS:This MFCM method has shown a new application in medical diagnosis.

根据高职高专医学院校学生综合学业成绩评价指标体系,以浙江医学高等专科学校为例,通过粗糙集简约理论和关联规则算法挖掘学生历史成绩数据,分析研究影响学生综合学业成绩的关键指标及相互间的关系,为高职高专医学院校综合评价学生学业状况提供参考.

In this paper, execution sequence of clinical pathway (CP) is abstracted with genetic algorithm (GA). For the purpose, implemental sequence from historical clinical event logs for necessary clinical activities in published CP is used as the gene values of each chromosome. Through probability computation in fitness function, the optimal sequence of CP for a certain hospital is abstracted which reflecting the actual execution of CP. The application in Primary lung cancer surgery has demonstrated the feasibility of the method.

[目的]探讨高职高专医学院校学生职业认同感与学习倦怠的关系. [方法]选取某高职高专医学院校临床专业(2个)和非临床相关专业(3个)680名在校生为研究对象,运用六维职业认同感问卷和三维学习倦怠量表进行调查,采用方差分析、相关分析和多元线性回归方法进行统计分析. [结果]方差分析结果表明,职业认同感问卷和学习倦怠量表各维度得分在不同个体特征间差异有统计学意义(P＜0.01).相关分析结果显示,高职高专医学生职业认同感与学习倦怠呈负相关,相关系数为-0.483;职业认同感与学习倦怠3个维度(情绪倦怠、发展倦怠和行为倦怠)相关系数分别是-0.430,-0.539和-0.270.多元线性回归分析表明,职业认同感与学习倦怠呈负相关. [结论]职业认同感对学习倦怠具有反向预测作用,职业认同感受不同专业、年级等因素的影响,提高高职高专医学生职业认同感,有助于降低学生学习倦怠.

目的:构建高职高专学生综合学业成绩评价指标体系.方法:以浙江医学高等专科学校教务管理系统中反映学生成绩的因素为基础,应用德尔菲法(Delphi Method)构建高职高专学生综合学业成绩评价指标体系,用层次分析法(Analytic Hierarchy Process,AHP)量化影响因素,在一致性检验的基础上确定各指标的权重向量.结果:经一致性检验制定评价指标体系.结论:该评价指标体系为高职高专院校多元化评价学生学业成绩提供参考.

Objective: To propose the improved GM(1,1)(Grey Model, 1st grey theoretical differential equation model) method to quickly predict long-short term total health expenditure(THE) in China, effectively shorten prediction time and improve the reliability of prediction. Methods: According to the changes of average underlying annual growth rate of historical THE, some aberrant points for years were calculated with GM(1,1) method. THE was predicted by linear regression model between two continuous aberrant years.Results: Compared with average annual growth rate, ARIMA model and quick calculation method, the result of prediction was more accurate and convenient. Conclusion: The prediction method for THE based on improved GM(1.1) model is rapid, effective and feasible.

本文从思想观念、高职高专特点、医学类专业特点和学分制本身特征四个方面深入探讨高职高专医学院校推行学分制的相关制约因素,以此总结现阶段试行学年学分制符合高职高专医学院校发展规律,是从学年制过渡到完全学分制的有效途径.

It becomes a hot issue how to implement credit system management in medical education at higher vocational schools.The article analyzes the main problems in the credit system based on the contents of higher education management.According to these factors,some educational management measurements are proposed to reform the credit system.

The stakeholder analysis has been extensively applied in health administration and the research of health policy,which has acquired preliminary achievements.In this paper,the author analyses the needs,contributions and goals of the main stakeholders and secondary stakeholders in the new rural CMS based on stakeholder theory,and construct an evaluation index system for it including 3 first level indexes,12 second level indexes,and 24 third level indexes.