Electronic health records (EHR) systematically represent patient data in digital form. However, text and visualization based EHR systems are poorly integrated in the hospital workflow due to their complex and rather non-intuitive access structure. This is especially disadvantageous in clinical cooperative situations that require an efficient, task specific information transfer.
In this paper we introduce a novel concept of anatomically integrated in-place visualization designed to engage with cooperative tasks on a neurosurgical ward. Based on the findings of our field studies and the derived design goals, we propose an approach that follows a visual tradition in medicine, which is tightly related with anatomy, by using a virtual patient's body as spatial representation of visually encoded abstract medical data. More specifically, we provide a generic set of formal requirements for these kinds of in-place visualizations, we apply these requirements in order to achieve a specific visualization of neurological symptoms related to the differential diagnosis of spinal disc herniation, and we present a prototypical implementation of the visualization concept on a mobile device. Moreover, we discuss various challenges related to visual encoding and visibility of the body model components. Finally, the prototype is evaluated by 10 neurosurgeons, who assess the validity and the further potential of the proposed approach.
Patient-centered visualization of multistage cancer treatment trajectories
University of Applied Sciences of the Grisons（格劳宾登应用科学大学）；Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden（德累斯顿工业大学卡尔·古斯塔夫·卡鲁斯大学附属医院）
A learning health system in Neurorehabilitation as a foundation for multimodal patient representation
Lake Lucerne Institute（卢塞恩湖研究所）；Spinal Cord and Artificial Intelligence (SCAI) Lab, ETH Zurich and Swiss Paraplegic Research（脊髓与人工智能（SCAI）实验室，苏黎世联邦理工学院和瑞士 paraplegic 研究）；Institute of Computational Biology, Helmholtz Center Munich（计算生物学研究所，赫尔霍兹慕尼黑中心）；Department of Mathematics, Technical University of Munich（数学系，慕尼黑工业大学）
Challenges in Synchronous & Remote Collaboration Around Visualization
University of Waterloo（滑铁卢大学）；The University of Queensland（昆士兰大学）；ENAC Université de Toulouse（图卢兹国立高等航空学院）；Ochanomizu University（御茶水女子大学）；University of Stuttgart（斯图加特大学）；Louisiana State University（路易斯安那州立大学）；Université Paris-Saclay, Inria, CNRS（巴黎萨克雷大学、法国国家信息与自动化研究所、法国国家科学研究中心）；JPMorganChase（摩根大通）；Simon Fraser University（西蒙菲莎大学）；University of Minnesota-Twin Cities（明尼苏达大学双城分校）；University of South Australia（南澳大学）；Monash University（莫纳什大学）
Verify, Offload, Extend & Recommend: Selective Complementarity in AI Support for Physical Activity Planning with Longitudinal Patient Data
Ludwig Boltzmann Institute for Digital Health and Prevention（路德维希·玻尔兹曼数字健康与预防研究所）；LMU Munich（慕尼黑大学）；LASIGE, Faculdade de Ciências, Universidade de Lisboa（里斯本大学理学院LASIGE）；Faculty of Human Kinetics, Universidade de Lisboa（里斯本大学人体运动学学院）
PhenoFlow: A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets
Seoul National University（首尔大学）；Korea University Guro Hospital（高丽大学九老医院）；Seoul National University College of Medicine（首尔大学医学院）；Seoul National University Bundang Hospital（首尔大学盆唐医院）；Hankuk University of Foreign Studies（韩国外国语大学）
EXR: An Interactive Immersive EHR Visualization in Extended Reality
Georgia Institute of Technology（佐治亚理工学院）；Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech & Emory University（佐治亚理工学院生物医学工程系及埃默里大学）；Shriners Hospitals for Children, Headquarters, Tampa, FL（夏普斯儿童医院，总部，佛罗里达州坦帕）；Shriners Hospitals for Children, Philadelphia, PA（夏普斯儿童医院，费城，宾夕法尼亚州）
