Data visualization in healthcare and medicine: a survey

Xunan Tan, Xiang Suo, Wenjun Li, Lei Bi, Fangshu Yao
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Abstract

Visualization analysis is crucial in healthcare as it provides insights into complex data and aids healthcare professionals in efficiency. Information visualization leverages algorithms to reduce the complexity of high-dimensional heterogeneous data, thereby enhancing healthcare professionals’ understanding of the hidden associations among data structures. In the field of healthcare visualization, efforts have been made to refine and enhance the utility of data through diverse algorithms and visualization techniques. This review aims to summarize the existing research in this domain and identify future research directions. We searched Web of Science, Google Scholar and IEEE Xplore databases, and ultimately, 76 articles were included in our analysis. We collected and synthesized the research findings from these articles, with a focus on visualization, artificial intelligence and supporting tasks in healthcare. Our study revealed that researchers from diverse fields have employed a wide range of visualization techniques to visualize various types of data. We summarized these visualization methods and proposed recommendations for future research. We anticipate that our findings will promote further development and application of visualization techniques in healthcare.

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医疗保健中的数据可视化:调查
可视化分析在医疗保健领域至关重要,因为它能让人们深入了解复杂的数据,帮助医疗保健专业人员提高效率。信息可视化利用算法降低高维异构数据的复杂性,从而增强医疗保健专业人员对数据结构之间隐藏关联的理解。在医疗保健可视化领域,人们一直在努力通过各种算法和可视化技术来完善和提高数据的实用性。本综述旨在总结该领域的现有研究,并确定未来的研究方向。我们搜索了 Web of Science、Google Scholar 和 IEEE Xplore 数据库,最终有 76 篇文章被纳入我们的分析。我们收集并综合了这些文章的研究成果,重点关注医疗保健中的可视化、人工智能和支持任务。我们的研究显示,来自不同领域的研究人员采用了多种可视化技术来实现各类数据的可视化。我们总结了这些可视化方法,并为未来研究提出了建议。我们预计,我们的研究结果将促进可视化技术在医疗保健领域的进一步发展和应用。
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