医疗保健中的计算资源

IF 6.4 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery Pub Date : 2021-11-12 DOI:10.1002/widm.1437
Neelam Sharma, Naorem Leimarembi Devi, Satakshi Gupta, G. Raghava
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引用次数: 1

摘要

医疗保健是人类生活中最重要的组成部分,因为每个人都希望拥有幸福、健康和富裕的生活。大多数科学分支都致力于改善医疗保健。在知识挖掘时代,信息学在各个研究领域发挥着至关重要的作用。因此,在过去的三十年中出现了广泛的基于信息学的领域,包括医学信息学、生物信息学、化学信息学、药物信息学、免疫信息学和临床信息学。在过去,许多评论都集中在基于信息学的领域在医疗保健中的应用。在这篇综述中,试图总结在任何基于信息学的领域中开发的主要计算资源,这些资源在医疗保健中有应用。本文综述了以下领域的计算资源——药物发现、毒性预测、疫苗设计、疾病生物标志物和物联网。我们主要关注免费可用的功能资源,如数据存储库、预测模型、独立软件、移动应用程序和web服务。为了向社区提供服务,我们开发了一个健康门户网站,维护与医疗保健相关的链接http://webs.iiitd.edu.in/。
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Computational resources in healthcare
Healthcare is the most important component in the life of all human beings as each individual wish to have happy, healthy, and wealthy life‐span. Most of the branches of science are dedicated to improve the healthcare. In the era of knowledge mining, informatics is playing a crucial role in different branches of research. Thus, a wide range of informatics‐based fields have emerged in the last three decades that include medical informatics, bioinformatics, cheminformatics, pharmacoinformatics, immunoinformatics, and clinical informatics. In the past, a number of reviews have been focused on the application of an informatics‐based field in the healthcare. In this review, an attempt is made to summarize the major computational resources developed in any informatics‐based field that have an application in healthcare. This review enlists computational resources in following groups ‐ drug discovery, toxicity prediction, vaccine designing, disease biomarkers, and Internet of Things. We mainly focused on freely available, functional resources like data repositories, prediction models, standalone software, mobile apps, and web services. In order to provide service to the community, we developed a health portal that maintain links related to healthcare http://webs.iiitd.edu.in/.
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来源期刊
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
22.70
自引率
2.60%
发文量
39
审稿时长
>12 weeks
期刊介绍: The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD) are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.
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