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Record W4221085077 · doi:10.3389/fsurg.2022.864792

Augmented Reality in Neurosurgery, State of Art and Future Projections. A Systematic Review

2022· review· en· W4221085077 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Surgery · 2022
Typereview
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAugmented realityMedicineNeurosurgeryNeuronavigationVirtual realityMedical physicsMedical educationSurgeryComputer scienceResectionArtificial intelligence

Abstract

fetched live from OpenAlex

Background: The use of augmented reality (AR) is growing in medical education, in particular, in radiology and surgery. AR has the potential to become a strategic component of neurosurgical training courses. In fact, over the years, there has been a progressive increase in the application of AR in the various fields of neurosurgery. In this study, the authors aim to define the diffusion of these augmented reality systems in recent years. This study describes future trends in augmented reality for neurosurgeons. Methods: A systematic review of the literature was conducted to identify research published from December 1st, 2011 to November 30th, 2021. Electronic databases (PubMed, PubMed Central, and Scopus) were screened. The methodological quality of studies and extracted data were assessed for "augmented reality" and "neurosurgery". The data analysis focused on the geographical distribution, temporal evolution, and topic of augmented reality in neurosurgery. Results: A total of 198 studies have been included. The number of augmented reality applications in the neurosurgical field has increased during the last 10 years. The main topics on which it is mostly applied are spine surgery, neuronavigation, and education. The geographical distribution shows extensive use of augmented reality in the USA, Germany, China, and Canada. North America is the continent that uses augmented reality the most in the training and education of medical students, residents, and surgeons, besides giving the greatest research contribution in spine surgery, brain oncology, and surgical planning. AR is also extensively used in Asia for intraoperative navigation. Nevertheless, augmented reality is still far from reaching Africa and other countries with limited facilities, as no publications could be retrieved from our search. Conclusions: The use of AR is significantly increased in the last 10 years. Nowadays it is mainly used in spine surgery and for neurosurgical education, especially in North America, Europe and China. A continuous growth, also in other aspects of the specialty, is expected in the next future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.298
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it