Evidence map›Paper›PMID 36826963›Full record

ArticleJournal of imaging2023

Translation of Medical AR Research into Clinical Practice.

Matthias Seibold, José Miguel Spirig, Hooman Esfandiari, Mazda Farshad, Philipp Fürnstahl

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. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Using Hologram-Based Augmented Reality in Anatomy Learning: The TEACHANATOMY Randomized Trial.Academic medicine : journal of the Association of American Medical Colleges · 2025
    Trial
  2. Article
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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

5 authors.

Matthias SeiboldResearch in Orthopedic Computer Science, Balgrist University Hospital, University of Zurich, CH-8008 Zurich, Switzerland.
José Miguel SpirigDepartment of Orthopedics, Balgrist University Hospital, University of Zurich, CH-8008 Zurich, Switzerland.
Hooman EsfandiariResearch in Orthopedic Computer Science, Balgrist University Hospital, University of Zurich, CH-8008 Zurich, Switzerland.
Mazda FarshadDepartment of Orthopedics, Balgrist University Hospital, University of Zurich, CH-8008 Zurich, Switzerland.
Philipp FürnstahlResearch in Orthopedic Computer Science, Balgrist University Hospital, University of Zurich, CH-8008 Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Translational research is aimed at turning discoveries from basic science into results that advance patient treatment. The translation of technical solutions into clinical use is a complex, iterative process that involves different stages of design, development, and validation, such as the identification of unmet clinical needs, technical conception, development, verification and validation, regulatory matters, and ethics. For this reason, many promising technical developments at the interface of technology, informatics, and medicine remain research prototypes without finding their way into clinical practice. Augmented reality is a technology that is now making its breakthrough into patient care, even though it has been available for decades. In this work, we explain the translational process for Medical AR devices and present associated challenges and opportunities. To the best knowledge of the authors, this concept paper is the first to present a guideline for the translation of medical AR research into clinical practice.

Indexed as

computer aided surgerymedical ARorthopedic surgerypedicle screw placementtranslational research

Identifiers

PMID36826963
PMCPMC9961816

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.