Visualization Techniques of Time-Oriented Data for the Comparison of Single Patients With Multiple Patients or Cohorts: Scoping Review.

BACKGROUND: Visual analysis and data delivery in the form of visualizations are of great importance in health care, as such forms of presentation can reduce errors and improve care and can also help provide new insights into long-term disease progression. Information visualization and visual analytics also address the complexity of long-term, time-oriented patient data by reducing inherent complexity and facilitating a focus on underlying and hidden patterns. OBJECTIVE: This review aims to provide an overview of visualization techniques for time-oriented data in health care, supporting the comparison of patients. We systematically collected literature and report on the visualization techniques supporting the comparison of time-based data sets of single patients with those of multiple patients or their cohorts and summarized the use of these techniques. METHODS: This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. After all collected articles were screened by 16 reviewers according to the criteria, 6 reviewers extracted the set of variables under investigation. The characteristics of these variables were based on existing taxonomies or identified through open coding. RESULTS: Of the 249 screened articles, we identified 22 (8.8%) that fit all criteria and reviewed them in depth. We collected and synthesized findings from these articles for medical aspects such as medical context, medical objective, and medical data type, as well as for the core investigated aspects of visualization techniques, interaction techniques, and supported tasks. The extracted articles were published between 2003 and 2019 and were mostly situated in clinical research. These systems used a wide range of visualization techniques, most frequently showing changes over time. Timelines and temporal line charts occurred 8 times each, followed by histograms with 7 occurrences and scatterplots with 5 occurrences. We report on the findings quantitatively through visual summarization, as well as qualitatively. CONCLUSIONS: The articles under review in general mitigated complexity through visualization and supported diverse medical objectives. We identified 3 distinct patient entities: single patients, multiple patients, and cohorts. Cohorts were typically visualized in condensed form, either through prior data aggregation or through visual summarization, whereas visualization of individual patients often contained finer details. All the systems provided mechanisms for viewing and comparing patient data. However, explicitly comparing a single patient with multiple patients or a cohort was supported only by a few systems. These systems mainly use basic visualization techniques, with some using novel visualizations tailored to a specific task. Overall, we found the visual comparison of measurements between single and multiple patients or cohorts to be underdeveloped, and we argue for further research in a systematic review, as well as the usefulness of a design space.

The Role of Community Health Workers Within the Continuum of Services for HIV, Viral Hepatitis, and Other STIs Amongst Men Who Have Sex with Men in Europe.

Little is known about Community Health Workers (CHWs) who work in non-clinical settings to provide sexual health support around HIV, viral hepatitis, and other sexually transmitted infections (STIs) to men who have sex with men (MSM) in Europe and neighbouring countries. This article describes for the first time, who CHWs are, and how they contribute to the continuum of services for HIV, viral hepatitis, and other STIs amongst MSM. The first European Community Health Worker Online Survey (ECHOES) developed in the framework of the EU-funded ESTICOM project ( www.esticom.eu ), was available in 16 languages (October 2017-January 2018). Amongst the 1035 persons aged 18 and older reporting CHW activities in the previous 12 months, 28.2% were women, 30.7% were volunteers, 59.2% were men self-defining as gay/homosexual, bisexual or queer ('peer CHWs'), and most CHWs worked/volunteered in private not-for-profit organisations (86.4%). CHWs involvement in the continuum of services for HIV, viral hepatitis and other STIs was as follows: primary prevention (88.6%), consultation and counselling (58.0%), testing provision (50.6%), linkage to care (49.8%), and treatment and support activities (51.3%). CHWs were also involved in cross-cutting activities such as developing interventions, advocacy, and engaging in research (46.3%). CHWs as a public health workforce contribute to all steps of the continuum of services for HIV, viral hepatitis, and other STIs amongst MSM in Europe. National governments should recognise and support CHWs better in order to make their activities more visible and sustainable, and increase their impact on the continuum of services.

Perception of Line Attributes for Visualization.

Line attributes such as width and dashing are commonly used to encode information. However, many questions on the perception of line attributes remain, such as how many levels of attribute variation can be distinguished or which line attributes are the preferred choices for which tasks. We conducted three studies to develop guidelines for using stylized lines to encode scalar data. In our first study, participants drew stylized lines to encode uncertainty information. Uncertainty is usually visualized alongside other data. Therefore, alternative visual channels are important for the visualization of uncertainty. Additionally, uncertainty-e.g., in weather forecasts-is a familiar topic to most people. Thus, we picked it for our visualization scenarios in study 1. We used the results of our study to determine the most common line attributes for drawing uncertainty: Dashing, luminance, wave amplitude, and width. While those line attributes were especially common for drawing uncertainty, they are also commonly used in other areas. In studies 2 and 3, we investigated the discriminability of the line attributes determined in study 1. Studies 2 and 3 did not require specific application areas; thus, their results apply to visualizing any scalar data in line attributes. We evaluated the just-noticeable differences (JND) and derived recommendations for perceptually distinct line levels. We found that participants could discriminate considerably more levels for the line attribute width than for wave amplitude, dashing, or luminance.

InVADo: Interactive Visual Analysis of Molecular Docking Data.

Molecular docking is a key technique in various fields like structural biology, medicinal chemistry, and biotechnology. It is widely used for virtual screening during drug discovery, computer-assisted drug design, and protein engineering. A general molecular docking process consists of the target and ligand selection, their preparation, and the docking process itself, followed by the evaluation of the results. However, the most commonly used docking software provides no or very basic evaluation possibilities. Scripting and external molecular viewers are often used, which are not designed for an efficient analysis of docking results. Therefore, we developed InVADo, a comprehensive interactive visual analysis tool for large docking data. It consists of multiple linked 2D and 3D views. It filters and spatially clusters the data, and enriches it with post-docking analysis results of protein-ligand interactions and functional groups, to enable well-founded decision-making. In an exemplary case study, domain experts confirmed that InVADo facilitates and accelerates the analysis workflow. They rated it as a convenient, comprehensive, and feature-rich tool, especially useful for virtual screening.

2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality.

Relational information between different types of entities is often modelled by a multilayer network (MLN) - a network with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however, the impact of the arrangement on the readability of the network is an open question. Therefore, we studied this impact for several commonly occurring tasks related to MLN analysis. Additionally, layer arrangements with a dimensionality beyond 2D, which are common in this scenario, motivate the use of stereoscopic displays. We ran a human subject study utilising a Virtual Reality headset to evaluate 2D, 2.5D, and 3D layer arrangements. The study employs six analysis tasks that cover the spectrum of an MLN task taxonomy, from path finding and pattern identification to comparisons between and across layers. We found no clear overall winner. However, we explore the task-to-arrangement space and derive empirical-based recommendations on the effective use of 2D, 2.5D, and 3D layer arrangements for MLNs.

GPU-powered tools boost molecular visualization.

Recent advances in experimental structure determination provide a wealth of structural data on huge macromolecular assemblies such as the ribosome or viral capsids, available in public databases. Further structural models arise from reconstructions using symmetry orders or fitting crystal structures into low-resolution maps obtained by electron-microscopy or small angle X-ray scattering experiments. Visual inspection of these huge structures remains an important way of unravelling some of their secrets. However, such visualization cannot conveniently be carried out using conventional rendering approaches, either due to performance limitations or due to lack of realism. Recent developments, in particular drawing benefit from the capabilities of Graphics Processing Units (GPUs), herald the next generation of molecular visualization solutions addressing these issues. In this article, we present advances in computer science and visualization that help biologists visualize, understand and manipulate large and complex molecular systems, introducing concepts that remain little-known in the bioinformatics field. Furthermore, we compile currently available software and methods enhancing the shape perception of such macromolecular assemblies, for example based on surface simplification or lighting ameliorations.

OmicsTIDE: interactive exploration of trends in multi-omics data.

Motivation: The increasing amount of data produced by omics technologies has enabled researchers to study phenomena across multiple omics layers. Besides data-driven analysis strategies, interactive visualization tools have been developed for a more transparent analysis. However, most state-of-the-art tools do not reconstruct the impact of a single omics layer on the integration result. Results: We developed a data classification scheme focusing on different aspects of multi-omics datasets for a systemic understanding. Based on this classification, we developed the Omics Trend-comparing Interactive Data Explorer (OmicsTIDE), an interactive visualization tool for the comparison of gene-based quantitative omics data. The tool consists of a computational part that clusters omics datasets to determine trends and an interactive visualization. The trends are visualized as profile plots and are connected by a Sankey diagram that allows for an interactive pairwise trend comparison to discover concordant and discordant trends. Moreover, large-scale omics datasets are broken down into small subsets that can be analyzed functionally using Gene Ontology enrichment within few analysis steps. We demonstrate the interactive analysis using OmicsTIDE with two case studies focusing on different experimental designs. Availability and implementation: OmicsTIDE is a web tool available via http://omicstide-tuevis.cs.uni-tuebingen.de/. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

ARGUS: Visualization of AI-Assisted Task Guidance in AR.

The concept of augmented reality (AR) assistants has captured the human imagination for decades, becoming a staple of modern science fiction. To pursue this goal, it is necessary to develop artificial intelligence (AI)-based methods that simultaneously perceive the 3D environment, reason about physical tasks, and model the performer, all in real-time. Within this framework, a wide variety of sensors are needed to generate data across different modalities, such as audio, video, depth, speech, and time-of-flight. The required sensors are typically part of the AR headset, providing performer sensing and interaction through visual, audio, and haptic feedback. AI assistants not only record the performer as they perform activities, but also require machine learning (ML) models to understand and assist the performer as they interact with the physical world. Therefore, developing such assistants is a challenging task. We propose ARGUS, a visual analytics system to support the development of intelligent AR assistants. Our system was designed as part of a multi-year-long collaboration between visualization researchers and ML and AR experts. This co-design process has led to advances in the visualization of ML in AR. Our system allows for online visualization of object, action, and step detection as well as offline analysis of previously recorded AR sessions. It visualizes not only the multimodal sensor data streams but also the output of the ML models. This allows developers to gain insights into the performer activities as well as the ML models, helping them troubleshoot, improve, and fine-tune the components of the AR assistant.

Nonclinical Sexual Health Support for HIV, Viral Hepatitis, and Other Sexually Transmitted Infections in Gay, Bisexual, and Other Men Who Have Sex With Men: Protocol for a European Community Health Worker Online Survey (ECHOES).

BACKGROUND: The term "community health worker" (CHW) can apply to a wide range of individuals providing health services and support for diverse populations. Very little is known about the role of CHWs in Europe working in nonclinical settings who promote sexual health and prevent HIV and other sexually transmitted infections (STIs) among gay, bisexual, and other men who have sex with men (MSM). OBJECTIVE: This paper describes the development and piloting of the first European Community Health Worker Online Survey (ECHOES) as part of the broader European Union-funded ESTICOM (European Surveys and Trainings to Improve MSM Community Health) project. The questionnaire aimed to assess the knowledge, attitudes, and practices of CHWs providing sexual health services to gay, bisexual, and other MSM in European settings. METHODS: ECHOES comprises three superordinate domains divided into 10 subsections with 175 items (routed) based on a scoping exercise and literature review, online prepiloting, and Europe-wide consultation. Additional piloting and cognitive debriefing interviews with stakeholders were conducted to identify comprehension issues and improve the clarity, intelligibility, accessibility, and acceptability of the survey. Psychometric properties, including internal consistency of the standardized scales used as part of the survey were examined. The final survey was available to 33 countries in 16 languages. RESULTS: Recruitment closed on January 31, 2018. Data from 1035 CHWs were available for analysis after application of the exclusion criteria. The findings of the ECHOES survey and the wider ESTICOM project, are now available from the ESTICOM website and/or by contacting the first author. CONCLUSIONS: The findings of this survey will help characterize, for the first time, the diverse role of CHWs who provide sexual health services to gay, bisexual, and other MSM in Europe. Importantly, the data will be used to inform the content and design of a dedicated training program for CHWs as part of the larger ESTICOM project and provide recommendations for MSM-specific strategies to improve sexual health in general and to reduce the incidence and prevalence of HIV, viral hepatitis, and other STIs in particular. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/15012.

Interactive visualization of molecular surface dynamics.

Molecular dynamics simulations of proteins play a growing role in various fields such as pharmaceutical, biochemical and medical research. Accordingly, the need for high quality visualization of these protein systems raises. Highly interactive visualization techniques are especially needed for the analysis of time-dependent molecular simulations. Beside various other molecular representations the surface representations are of high importance for these applications. So far, users had to accept a trade-off between rendering quality and performance--particularly when visualizing trajectories of time-dependent protein data. We present a new approach for visualizing the Solvent Excluded Surface of proteins using a GPU ray casting technique and thus achieving interactive frame rates even for long protein trajectories where conventional methods based on precomputation are not applicable. Furthermore, we propose a semantic simplification of the raw protein data to reduce the visual complexity of the surface and thereby accelerate the rendering without impeding perception of the protein's basic shape. We also demonstrate the application of our Solvent Excluded Surface method to visualize the spatial probability density for the protein atoms over the whole period of the trajectory in one frame, providing a qualitative analysis of the protein flexibility.

Feature-Based Volumetric Terrain Generation and Decoration.

Two-dimensional height fields are the most common data structure used for storing and rendering of terrain in offline rendering and especially real-time computer graphics. By its very nature, a height field cannot store terrain structures with multiple vertical layers such as overhanging cliffs, caves, or arches. This restriction does not apply to volumetric data structures. However, the workflow of manual modelling and editing of volumetric terrain usually is tedious and very time-consuming. Therefore, we propose to use three-dimensional curve-based primitives to efficiently model prominent, large-scale terrain features. We present a technique for volumetric generation of a complete terrain surface from the sparse input data by means of diffusion-based algorithms. By combining an efficient, feature-based toolset with a volumetric terrain representation, the modelling workflow is accelerated and simplified while retaining the full artistic freedom of volumetric terrains. Feature Curves also contain material information that can be complemented with local details by using per-face texture mapping. All stages of our method are GPU-accelerated using compute shaders to ensure interactive editing of terrain. Please note that this paper is an extended version of our previously published work [1] .

Molecular Graphics: Bridging Structural Biologists and Computer Scientists.

Visualization of molecular structures is one of the most common tasks carried out by structural biologists, typically using software, such as Chimera, COOT, PyMOL, or VMD. In this Perspective article, we outline how past developments in computer graphics and data visualization have expanded the understanding of biomolecular function, and we summarize recent advances that promise to further transform structural biology. We also highlight how progress in molecular graphics has been impeded by communication barriers between two communities: the computer scientists driving these advances, and the structural and computational biologists who stand to benefit. By pointing to canonical papers and explaining technical progress underlying new graphical developments in simple terms, we aim to improve communication between these communities; this, in turn, would help shape future developments in molecular graphics.

From Virtual Reality to Immersive Analytics in Bioinformatics.

Bioinformatics-related research produces huge heterogeneous amounts of data. This wealth of information includes data describing metabolic mechanisms and pathways, proteomics, transcriptomics, and metabolomics. Often, the visualization and exploration of related structural - usually molecular - data plays an important role in the aforementioned contexts. For decades, virtual reality (VR)-related technologies were developed and applied to Bioinformatics problems. Often, these approaches provide "just" visual support of the analysis, e.g. in the case of exploring and interacting with a protein on a 3D monitor and compatible interaction hardware. Moreover, in the past these approaches were limited to cost-intensive professional visualization facilities. The advent of new affordable, and often mobile technologies, provides high potential for using similar approaches on a regular basis for daily research. Visual Analytics is successfully being used for several years to analyze complex and heterogeneous datasets. Immersive Analytics combines these approaches now with new immersive and interactive technologies. This publication provides a short overview of related technologies, their history and Bioinformatics-related approaches. Six new applications on the path from VR to Immersive Analytics are being introduced and discussed.

10 Years of MegaMol: The Pain and Gain of Creating Your Own Visualization Framework.

This article discusses our experience in creating MegaMol, an open-source visualization framework for large particle-based data.

Interactive Molecular Graphics for Augmented Reality Using HoloLens.

Immersive technologies like stereo rendering, virtual reality, or augmented reality (AR) are often used in the field of molecular visualisation. Modern, comparably lightweight and affordable AR headsets like Microsoft's HoloLens open up new possibilities for immersive analytics in molecular visualisation. A crucial factor for a comprehensive analysis of molecular data in AR is the rendering speed. HoloLens, however, has limited hardware capabilities due to requirements like battery life, fanless cooling and weight. Consequently, insights from best practises for powerful desktop hardware may not be transferable. Therefore, we evaluate the capabilities of the HoloLens hardware for modern, GPU-enabled, high-quality rendering methods for the space-filling model commonly used in molecular visualisation. We also assess the scalability for large molecular data sets. Based on the results, we discuss ideas and possibilities for immersive molecular analytics. Besides more obvious benefits like the stereoscopic rendering offered by the device, this specifically includes natural user interfaces that use physical navigation instead of the traditional virtual one. Furthermore, we consider different scenarios for such an immersive system, ranging from educational use to collaborative scenarios.

Enabling Detailed, Biophysics-Based Skeletal Muscle Models on HPC Systems.

Realistic simulations of detailed, biophysics-based, multi-scale models often require very high resolution and, thus, large-scale compute facilities. Existing simulation environments, especially for biomedical applications, are typically designed to allow for high flexibility and generality in model development. Flexibility and model development, however, are often a limiting factor for large-scale simulations. Therefore, new models are typically tested and run on small-scale compute facilities. By using a detailed biophysics-based, chemo-electromechanical skeletal muscle model and the international open-source software library OpenCMISS as an example, we present an approach to upgrade an existing muscle simulation framework from a moderately parallel version toward a massively parallel one that scales both in terms of problem size and in terms of the number of parallel processes. For this purpose, we investigate different modeling, algorithmic and implementational aspects. We present improvements addressing both numerical and parallel scalability. In addition, our approach includes a novel visualization environment which is based on the MegaMol framework and is capable of handling large amounts of simulated data. We present the results of a number of scaling studies at the Tier-1 supercomputer HazelHen at the High Performance Computing Center Stuttgart (HLRS). We improve the overall runtime by a factor of up to 2.6 and achieve good scalability on up to 768 cores.

Molecular Surface Maps.

We present Molecular Surface Maps, a novel, view-independent, and concise representation for molecular surfaces. It transfers the well-known world map metaphor to molecular visualization. Our application maps the complex molecular surface to a simple 2D representation through a spherical intermediate, the Molecular Surface Globe. The Molecular Surface Map concisely shows arbitrary attributes of the original molecular surface, such as biochemical properties or geometrical features. This results in an intuitive overview, which allows researchers to assess all molecular surface attributes at a glance. Our representation can be used as a visual summarization of a molecule's interface with its environment. In particular, Molecular Surface Maps simplify the analysis and comparison of different data sets or points in time. Furthermore, the map representation can be used in a Space-time Cube to analyze time-dependent data from molecular simulations without the need for animation. We show the feasibility of Molecular Surface Maps for different typical analysis tasks of biomolecular data.

MegaMol--A Prototyping Framework for Particle-Based Visualization.

Visualization applications nowadays not only face increasingly larger datasets, but have to solve increasingly complex research questions. They often require more than a single algorithm and consequently a software solution will exceed the possibilities of simple research prototypes. Well-established systems intended for such complex visual analysis purposes have usually been designed for classical, mesh-based graphics approaches. For particle-based data, however, existing visualization frameworks are too generic - e.g. lacking possibilities for consistent low-level GPU optimization for high-performance graphics - and at the same time are too limited - e.g. by enforcing the use of structures suboptimal for some computations. Thus, we developed the system softwareMegaMol for visualization research on particle-based data. On the one hand, flexible data structures and functional module design allow for easy adaption to changing research questions, e.g. studying vapors in thermodynamics, solid material in physics, or complex functional macromolecules like proteins in biochemistry. Therefore, MegaMol is designed as a development framework. On the other hand, common functionality for data handling and advanced rendering implementations are available and beneficial for all applications. We present several case studies of work implemented using our system as well as a comparison to other freely available or open source systems.

Visualising intrinsic disorder and conformational variation in protein ensembles.

Intrinsically disordered regions (IDRs) in proteins are still not well understood, but are increasingly recognised as important in key biological functions, as well as in diseases. IDRs often confound experimental structure determination-however, they are present in many of the available 3D structures, where they exhibit a wide range of conformations, from ill-defined and highly flexible to well-defined upon binding to partner molecules, or upon post-translational modifications. Analysing such large conformational variations across ensembles of 3D structures can be complex and difficult; our goal in this paper is to improve this situation by augmenting traditional approaches (molecular graphics and principal components) with methods from human-computer interaction and information visualisation, especially parallel coordinates. We present a new tool integrating these approaches, and demonstrate how it can dissect ensembles to reveal functional insights into conformational variation and intrinsic disorder.

Visual analysis for space-time aggregation of biomolecular simulations.

Conducting a current through a nanopore allows for the analysis of molecules inside the pore because a current modulation caused by the electrostatic properties of the passing molecules can be measured. This mechanism shows great potential for DNA sequencing, as the four different nucleotide bases induce different current modulations. We present a visualisation approach to investigate this phenomenon in our simulations of DNA within a nanopore by combining state-of-the-art molecular visualisation with vector field illustration. By spatial and temporal aggregation of the ions transported through the pore, we construct a velocity field which exhibits the induced current modulations caused by ion flux. In our interactive analysis using parametrisable three-dimensional visualisations, we encountered regions where the ion motion unexpectedly opposes the direction of the applied electric field.