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肿瘤学数据可视化中的视觉感知与前注意属性

Visual Perception and Pre-Attentive Attributes in Oncological Data Visualisation.

作者信息

Fusco Roberta, Granata Vincenza, Setola Sergio Venanzio, Pupo Davide, Petrosino Teresa, Lamanna Ciro Paolo, Castaldo Mimma, Riga Maria Giovanna, Karaboue Michele A, Izzo Francesco, Petrillo Antonella

机构信息

Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.

Unit of "Progettazione e Manutenzione Edile ed impianti", Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli, 80131 Naples, Italy.

出版信息

Bioengineering (Basel). 2025 Jul 18;12(7):782. doi: 10.3390/bioengineering12070782.

Abstract

In the era of precision medicine, effective data visualisation plays a pivotal role in supporting clinical decision-making by translating complex, multidimensional datasets into intuitive and actionable insights. This paper explores the foundational principles of visual perception, with a specific focus on pre-attentive attributes such as colour, shape, size, orientation, and spatial position, which are processed automatically by the human visual system. Drawing from cognitive psychology and perceptual science, we demonstrate how these attributes can enhance the clarity and usability of medical visualisations, reducing cognitive load and improving interpretive speed in high-stakes clinical environments. Through detailed case studies and visual examples, particularly within the field of oncology, we highlight best practices and common pitfalls in the design of dashboards, nomograms, and interactive platforms. We further examine the integration of advanced tools-such as genomic heatmaps and temporal timelines-into multidisciplinary workflows to support personalised care. Our findings underscore that visually intelligent design is not merely an aesthetic concern but a critical factor in clinical safety, efficiency, and communication, advocating for user-centred and evidence-based approaches in the development of health data interfaces.

摘要

在精准医学时代,有效的数据可视化通过将复杂的多维数据集转化为直观且可操作的见解,在支持临床决策方面发挥着关键作用。本文探讨视觉感知的基本原理,特别关注诸如颜色、形状、大小、方向和空间位置等前注意属性,这些属性由人类视觉系统自动处理。借鉴认知心理学和感知科学,我们展示了这些属性如何提高医学可视化的清晰度和可用性,在高风险临床环境中减轻认知负担并提高解读速度。通过详细的案例研究和视觉示例,特别是在肿瘤学领域,我们突出了仪表板、列线图和交互式平台设计中的最佳实践和常见陷阱。我们进一步研究将基因组热图和时间轴等先进工具整合到多学科工作流程中以支持个性化医疗。我们的研究结果强调,视觉智能设计不仅是美学问题,更是临床安全、效率和沟通的关键因素,倡导在健康数据接口开发中采用以用户为中心和基于证据的方法。

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