Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Neuroradiol J. 2024 Aug;37(4):418-433. doi: 10.1177/19714009231193158. Epub 2023 Aug 2.
The simplest approach to convey the results of scientific analysis, which can include complex comparisons, is typically through the use of visual items, including figures and plots. These statistical plots play a critical role in scientific studies, making data more accessible, engaging, and informative. A growing number of visual representations have been utilized recently to graphically display the results of oncologic imaging, including radiomic and radiogenomic studies. Here, we review the applications, distinct properties, benefits, and drawbacks of various statistical plots. Furthermore, we provide neuroradiologists with a comprehensive understanding of how to use these plots to effectively communicate analytical results based on imaging data.
传达科学分析结果的最简单方法通常是通过使用视觉元素,包括图表和图形,其中可能包括复杂的比较。这些统计图形在科学研究中起着至关重要的作用,使数据更易于访问、吸引人和提供信息。最近,越来越多的可视化表示被用于直观地显示肿瘤成像的结果,包括放射组学和放射基因组学研究。在这里,我们回顾了各种统计图形的应用、独特的属性、优点和缺点。此外,我们为神经放射科医生提供了全面的了解,帮助他们基于成像数据有效地使用这些图形来传达分析结果。