利用双聚类算法探测内科学知识基础及研究前沿

目的：利用双聚类算法探测内科学知识基础及研究前沿。方法：收集内科学高影响力杂志的数据,利用gCLUTO软件对数据进行双聚类分析,获取内科学领域知识基础和学科前沿。结果：近年来内科学的研究前沿表现为6个方面,临床流行病学和循证医学越来越多地与临床医学结合,成为临床研究者关注的方向。结论：双聚类算法在探测学科知识基础及研究前沿具有可行性,在未来的研究中,可以尝试将双聚类算法推广到各领域的学科发展评价中。     

基于双聚类方法的国际电子健康素养领域研究热点分析

通过双聚类分析方法探讨国际电子健康素养领域研究热点,具体包括电子健康素养与医疗卫生服务研究、干预研究、实证调查研究、量表开发与验证研究、基于互联网的健康相关行为研究,以期为我国电子健康素养研究提供参考。     

基于双向聚类分析的国际转化医学研究热点分析

以PubMed为数据源，运用双向聚类软件对近10年国际转化医学研究文献进行分析，绘制知识图谱，从情报学视角解读该领域研究热点和发展趋势，揭示出7个热点研究方向，以期为国内相关研究和管理人员提供参考。     

基于双向聚类方法的中医治疗中风病方剂配伍规律知识发现

目的深入探索方剂的制方要素,总结方药证治规律,找到对其中药理起关键作用的核心药/药组,为方剂配伍理论研究、药性理论研究、中医临床用药研究提供新方法和现代技术手段。方法从《中国方剂数据库》和《方剂现代应用数据库》中获取治疗中风病的方药文本数据源,经预处理、信息抽取后构建方药矩阵,引入双向聚类方法对方-药两方面数据同时聚类。结果预处理后得到有效记录648首,共计6913味药,生成了100×648“方-药”矩阵,最后得到4组聚类指标,高描述度代表方共8首,总结出针对不同证型配伍用药特点及各证型辨证论治的治则治法及各型常用药对药组。结论本方法适用于中医方剂数据库中方-药知识发现,可有效抽取所需方药信息,梳理出方药证治规律。     

BAREB: A Bayesian repulsive biclustering model for periodontal data

Preventing periodontal diseases (PD) and maintaining the structure and function of teeth are important goals for personal oral care. To understand the heterogeneity in patients with diverse PD patterns, we develop a Bayesian repulsive biclustering method that can simultaneously cluster the PD patients and their tooth sites after taking the patient- and site-level covariates into consideration. BAREB uses the determinantal point process prior to induce diversity among different biclusters to facilitate parsimony and interpretability. Since PD progression is hypothesized to be spatially referenced, BAREB factors in the spatial dependence among tooth sites. In addition, since PD is the leading cause for tooth loss, the missing data mechanism is nonignorable. Such nonrandom missingness is incorporated into BAREB. For the posterior inference, we design an efficient reversible jump Markov chain Monte Carlo sampler. Simulation studies show that BAREB is able to accurately estimate the biclusters, and compares favorably to alternatives. For real world application, we apply BAREB to a dataset from a clinical PD study, and obtain desirable and interpretable results. A major contribution of this article is the Rcpp implementation of our methodology, available in the R package BAREB .     

利用共词分析挖掘国际护理信息学研究热点

对PubMed收录的护理信息学领域的文献进行共词双聚类分析,探究该领域研究热点,绘制战略坐标图,展示这些研究热点的发展现状和趋势,为该领域研究人员了解护理信息学现状以及开展相关研究提供参考.     

Feature representation in the biclustering of symptom-herb relationship in Chinese medicine

Objective  

To find an appropriate feature representation in the biclustering of symptom-herb relationship in Chinese medicine (CM).     

Research hotspot and trend of chronic wounds: A bibliometric analysis from 2013 to 2022

Chronic wounds have been confirmed as a vital health problem facing people in the global population aging process. While significant progress has been achieved in the study of chronic wounds, the treatment effect should be further improved. The number of publications regarding chronic wounds has been rising rapidly. In this study, bibliometric analysis was conducted to explore the hotspots and trends in the research on chronic wounds. All relevant studies on chronic wounds between 2013 and 2022 were collected from the PubMed database of the Web of Science (WOS) and the National Center for Biotechnology Information (NCBI). The data were processed and visualised using a series of software. On that basis, more insights can be gained into hotspots and trends of this research field. Wound Repair and Regeneration has the highest academic achievement in the field of chronic wound research. The United States has been confirmed as the most productive country, and the University of California System ranks high among other institutions. Augustin, M. is the author of the most published study, and Frykberg, RG et al. published the most cited study. Furthermore, the hotspots of wound research over the last decade were identified (e.g., bandages, infection and biofilms, pathophysiology and therapy). This study will help researchers gain insights into chronic wound research's hotspots and trends accurately and quickly. Moreover, the exploration of bacterial biofilm and the pathophysiological mechanism of the chronic wound will lay a solid foundation and clear direction for treating chronic wounds.