Evidence map›Paper›PMID 38248988›Full record

ArticleJournal of imaging2023

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

Jing Ng, David Arness, Ashlee Gronowski, Zhonglin Qu, Chng Wei Lau, Daniel Catchpoole, Quang Vinh Nguyen

Abstract read
In one paragraph

Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jing NgSchool of Psychology, Western Sydney University, Penrith, NSW 2750, Australia.
David ArnessSchool of Psychology, Western Sydney University, Penrith, NSW 2750, Australia.
Ashlee GronowskiSchool of Psychology, Western Sydney University, Penrith, NSW 2750, Australia.
Zhonglin QuSchool of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0003-4500-004X
Chng Wei LauSchool of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0002-9652-134X
Daniel CatchpooleTumour Bank, Children's Cancer Research Unit, Kids Research, The Children's Hospital at Westmead, Westmead, NSW 2145, Australia.ORCID 0000-0001-5836-1413
Quang Vinh NguyenSchool of Computer, Data and Mathematical Sciences and MARCS Institute, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0002-0815-6224

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

biomedical dataegocentric visualizationexocentric visualizationvirtual environmentvirtual reality

Identifiers

PMID38248988
PMCPMC10817309

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.