Virtual reality for the observation of oncology models (VROOM): immersive analytics for oncology patient cohorts

Visualization and exploration of linked data using virtual reality

In this report, we analyse the use of virtual reality (VR) as a method to navigate and explore complex knowledge graphs. Over the past few decades, linked data technologies [Resource Description Framework (RDF) and Web Ontology Language (OWL)] have shown to be valuable to encode such graphs and many tools have emerged to interactively visualize RDF. However, as knowledge graphs get larger, most of these tools struggle with the limitations of 2D screens or 3D projections. Therefore, in this paper, we evaluate the use of VR to visually explore SPARQL Protocol and RDF Query Language (SPARQL) (construct) queries, including a series of tutorial videos that demonstrate the power of VR (see Graph2VR tutorial playlist: https://www.youtube.com/playlist?list=PLRQCsKSUyhNIdUzBNRTmE-_JmuiOEZbdH). We first review existing methods for Linked Data visualization and then report the creation of a prototype, Graph2VR. Finally, we report a first evaluation of the use of VR for exploring linked data graphs. Our results show that most participants enjoyed testing Graph2VR and found it to be a useful tool for graph exploration and data discovery. The usability study also provides valuable insights for potential future improvements to Linked Data visualization in VR.

Research Trends and Highlights Toward Virtual Reality in Patients With Cancer: Bibliometric Analysis

This retrospective bibliometric analysis was conducted to explore research trends and identify studies in fields of nursing, virtual reality, and cancer. Data were obtained from the Web of Science database using an advanced search strategy. The study data were analyzed using the R Studio software and visualized using VOSviewer. A total of 594 studies were retrieved and analyzed from January 1995 to December 2021. It was determined that 59.4% of the studies were research articles and that these studies had been conducted by 2771 authors. The reviewed studies were produced by researchers from 25 countries and were published in 29 different journals. Of these, 169 were conducted by researchers in the United States. "Virtual reality" and "nursing" were found to be prominent topics. Studies on virtual reality in patients with cancer in the field of nursing have increased over the past 8 years. Researchers have actively conducted studies in this field. Prominent studies have covered various patients with cancer in all age groups and palliative care processes. It was seen that the majority of the studies were randomized controlled trials, reviews, and systematic reviews. In addition, studies have used virtual reality as a distraction method in the management of symptoms in patients with breast, lung, and pediatric cancers undergoing chemotherapy treatment. This study provides a detailed and up-to-date analysis of the findings obtained from the Web of Science database by emphasizing bibliometric models of virtual reality technologies in nursing patients with cancer. We believe that the current data on the use of virtual reality applications in patients with cancer will guide the clinical practice and scientific studies of healthcare professionals.

Exocentric and Egocentric Views for Biomedical Data Analytics in Virtual Environments-A Usability Study

Biomedical datasets are usually large and complex, containing biological information about a disease. Computational analytics and the interactive visualisation of such data are essential decision-making tools for disease diagnosis and treatment. Oncology data models were observed in a virtual reality environment to analyse gene expression and clinical data from a cohort of cancer patients. The technology enables a new way to view information from the outside in (exocentric view) and the inside out (egocentric view), which is otherwise not possible on ordinary displays. This paper presents a usability study on the exocentric and egocentric views of biomedical data visualisation in virtual reality and their impact on usability on human behaviour and perception. Our study revealed that the performance time was faster in the exocentric view than in the egocentric view. The exocentric view also received higher ease-of-use scores than the egocentric view. However, the influence of usability on time performance was only evident in the egocentric view. The findings of this study could be used to guide future development and refinement of visualisation tools in virtual reality.

Understanding cancer patient cohorts in virtual reality environment for better clinical decisions: a usability study

BACKGROUND

Visualising patient genomic data in a cohort with embedding data analytics models can provide relevant and sensible patient comparisons to assist a clinician with treatment decisions. As immersive technology is actively used around the medical world, there is a rising demand for an efficient environment that can effectively display genomic data visualisations on immersive devices such as a Virtual Reality (VR) environment. The VR technology will allow clinicians, biologists, and computer scientists to explore a cohort of individual patients within the 3D environment. However, demonstrating the feasibility of the VR prototype needs domain users' feedback for future user-centred design and a better cognitive model of human-computer interactions. There is limited research work for collecting and integrating domain knowledge into the prototype design.

OBJECTIVE

A usability study for the VR prototype--Virtual Reality to Observe Oncology data Models (VROOM) was implemented. VROOM was designed based on a preliminary study among medical users. The goals of this usability study included establishing a baseline of user experience, validating user performance measures, and identifying potential design improvements that are to be addressed to improve efficiency, functionality, and end-user satisfaction.

METHODS

The study was conducted with a group of domain users (10 males, 10 females) with portable VR devices and camera equipment. These domain users included medical users such as clinicians and genetic scientists and computing domain users such as bioinformatics and data analysts. Users were asked to complete routine tasks based on a clinical scenario. Sessions were recorded and analysed to identify potential areas for improvement to the data visual analytics projects in the VR environment. The one-hour usability study included learning VR interaction gestures, running visual analytics tool, and collecting before and after feedback. The feedback was analysed with different methods to measure effectiveness. The statistical method Mann-Whitney U test was used to analyse various task performances among the different participant groups, and multiple data visualisations were created to find insights from questionnaire answers.

RESULTS

The usability study investigated the feasibility of using VR for genomic data analysis in domain users' daily work. From the feedback, 65% of the participants, especially clinicians (75% of them), indicated that the VR prototype is potentially helpful for domain users' daily work but needed more flexibility, such as allowing them to define their features for machine learning part, adding new patient data, and importing their datasets in a better way. We calculated the engaged time for each task and compared them among different user groups. Computing domain users spent 50% more time exploring the algorithms and datasets than medical domain users. Additionally, the medical domain users engaged in the data visual analytics parts (approximately 20%) longer than the computing domain users.

Technologies for whole-cell modeling: Genome-wide reconstruction of a cell in silico

With advances in high-throughput, large-scale in vivo measurement and genome modification techniques at the single-nucleotide level, there is an increasing demand for the development of new technologies for the flexible design and control of cellular systems. Computer-aided design is a powerful tool to design new cells. Whole-cell modeling aims to integrate various cellular subsystems, determine their interactions and cooperative mechanisms, and predict comprehensive cellular behaviors by computational simulations on a genome-wide scale. It has been applied to prokaryotes, yeasts, and higher eukaryotic cells, and utilized in a wide range of applications, including production of valuable substances, drug discovery, and controlled differentiation. Whole-cell modeling, consisting of several thousand elements with diverse scales and properties, requires innovative model construction, simulation, and analysis techniques. Furthermore, whole-cell modeling has been extended to multiple scales, including high-resolution modeling at the single-nucleotide and single-amino acid levels and multicellular modeling of tissues and organs. This review presents an overview of the current state of whole-cell modeling, discusses the novel computational and experimental technologies driving it, and introduces further developments toward multihierarchical modeling on a whole-genome scale.

Implications of immersive technologies in healthcare sector and its built environment

Objectives

This research focuses on how built environment experts can contribute to the MXR-enabled digital innovation as part of the multidisciplinary team effort to ensure post-pandemic resilience in healthcare built environment. The goal of this research is to help healthcare providers, built environment experts, and policy makers respectively: (1) Advocate the benefits of MXR for innovating health and social care; (2) Spark debate across networks of expertise to create health-promoting environment; and (3) Understand the overriding priorities in making effective pathways to the implementation of MXR.

Methods

To highlight the novelty of this research, the study relies on two qualitative methodologies: exploratory literature review and semi-structured interviews. Based on the evaluation of prior works and cross-national case studies, hypotheses are formulated from three arenas: (1) Cross-sectional Initiatives for Post-pandemic Resilience; (2) Interoperability and Usability of Next-gen Medicines; and (3) Metaverse and New Forms of Value in Future Healthcare Ecosystems. To verify those hypotheses, empirical findings are derived from in-depth interviews with nine key informants.

Results

The main findings are summarized under the following three themes: (1) Synergism between Architecture and Technology; (2) Patient Empowerment and Staff Support; and (3) Scalable Health and Wellbeing in Non-hospital and Therapeutic Settings. Firstly, both built environment and healthcare sectors can benefit from the various capabilities of MXR through cross-sectional initiatives, evidence-based practices, and participatory approaches. Secondly, a confluence of knowledge and methods of HCI and HBI can increase the interoperability and usability of MXR for the patient-centered and value-based healthcare models. Thirdly, the MXR-enabled technological regime will largely affect the new forms of value in healthcare premises by fostering more decentralized, preventive, and therapeutic characteristics in the future healthcare ecosystems.

Conclusion

Whether it's virtual or physical, our healthcare systems have placed great emphasis on the rigor of evidence-based approach linking health outcome to a clinical environment. Henceforth, built environment experts should seek closer ties with the MXR ecosystems for the co-production of scalable health and wellbeing in non-hospital and therapeutic settings. Ultimately, this is to improve resource efficiency in the healthcare sector while considering the transition of health resources towards in silico status by increasing the implementation of MXR.