Call for papers: Special issue on unlocking genetic diseases by integrating machine learning techniques and medical data

IF 7.7 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Big Data Mining and Analytics Pub Date : 2021-03-12 DOI:10.26599/BDMA.2021.9020005

引用次数: 0

Abstract

Big Data Mining and Analytics is an international academic journal sponsored by Tsinghua University and published quarterly. It features on technologies to enable and accelerate big data discovery. All of papers published are on the IEEE Xplore Digital Library with the open access mode. The journal is indexed and abstracted in Ei Compendex, Scopus, DBLP Computer Science, Google Scholar, and CNKI.

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论文征集：通过整合机器学习技术和医学数据解锁遗传疾病特刊

《大数据挖掘与分析》是清华大学主办的国际学术期刊，每季度出版一期。它的特点是能够实现和加速大数据发现的技术。所有发表的论文都是在开放存取模式下的IEEE Xplore数字图书馆上发表的。该期刊在Ei Compendex、Scopus、DBLP Computer Science、Google Scholar和CNKI中进行了索引和摘要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data Mining and Analytics Computer Science-Computer Science Applications

CiteScore

20.90

自引率

2.20%

发文量

期刊介绍： Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge. Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications. Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more. With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.