Dieter Julia, Ahlbrandt Janko, Knurr Alexander, Al-Hmad Janine, Ückert Frank
Division of Medical Informatics for Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany.
Stud Health Technol Inform. 2019 Aug 21;264:98-102. doi: 10.3233/SHTI190191.
With the growing interdisciplinarity of cancer treatment and increasing amounts of data and patients, it is getting increasingly difficult for physicians to capture a patient's medical history as a basis for adequate treatment and to compare different medical histories of similar patients to each other. Furthermore, in order to tackle the etiological mechanisms of cancer, it is crucial to identify patients exhibiting a different disease course than their corresponding cohort. Several timeline visualizations have already been proposed. However, the functions and design of such visualizations are always use case dependent. We constructed a cohort timeline prototype mock-up for a specific oncological use case involving multiple myeloma, where the chronological monitoring of various parameters is crucial for patient diagnosis and treatment. Our proposed cohort timeline is a synthesis between elements described in the literature and our own approaches regarding function and design.
随着癌症治疗跨学科性的不断增强以及数据量和患者数量的日益增加，医生越来越难以获取患者的病史作为适当治疗的依据，也难以将相似患者的不同病史相互比较。此外，为了探究癌症的病因机制，识别疾病进程与相应队列不同的患者至关重要。已经提出了几种时间线可视化方法。然而，此类可视化的功能和设计总是取决于具体用例。我们针对一个涉及多发性骨髓瘤的特定肿瘤学用例构建了一个队列时间线原型模型，其中对各种参数的时间顺序监测对于患者诊断和治疗至关重要。我们提出的队列时间线是文献中描述的元素与我们自己在功能和设计方面方法的综合。
