Precision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots.
Precision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots.
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DOI：
10.1109/tvcg.2018.2817557
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发表时间：
2019-04
影响因子：
5.2
通讯作者：
Fuller CD
中科院分区：
文献类型：
--
作者：
Marai GE;Ma C;Burks AT;Pellolio F;Canahuate G;Vock DM;Mohamed ASR;Fuller CD
我们提出了用于癌症治疗分析的集成问题解决环境的设计和评估。该环境将统计鞅模型和 K 最近邻方法与视觉编码（包括新颖的交互式列线图）交织在一起，以便计算和解释患者的生存概率作为类似患者结果的函数。协调的视图范式使得能够从大型头颈癌存储库中探索多变量、异质和少值的数据。视觉脚手架方法进一步使用户能够从熟悉的表示形式构建到不熟悉的表示形式。与领域专家的评估表明，这种可视化方法和一套简化的工作流程如何能够在类似患者群体的背景下系统、精确地分析患者预后。我们描述了从这次成功的多站点远程协作中汲取的设计经验教训。
We present the design and evaluation of an integrated problem solving environment for cancer therapy analysis. The environment intertwines a statistical martingale model and a K Nearest Neighbor approach with visual encodings, including novel interactive nomograms, in order to compute and explain a patient’s probability of survival as a function of similar patient results. A coordinated views paradigm enables exploration of the multivariate, heterogeneous and few-valued data from a large head and neck cancer repository. A visual scaffolding approach further enables users to build from familiar representations to unfamiliar ones. Evaluation with domain experts show how this visualization approach and set of streamlined workflows enable the systematic and precise analysis of a patient prognosis in the context of cohorts of similar patients. We describe the design lessons learned from this successful, multi-site remote collaboration.