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Record W4386564756 · doi:10.1177/17455057231199040

The Role of Three-dimensional Printed Models in Women’s Health

2023· review· en· W4386564756 on OpenAlexaff
Afnan Maher Hoory AlRawi, Tasneem Basha, Ahmed O. Elmeligy, Noha A. Mousa, Ghada Mohammed

Bibliographic record

VenueWomen s Health · 2023
Typereview
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcGill University
FundersUniversity of Sharjah
Keywords3d printedMedicineBiomedical engineering

Abstract

fetched live from OpenAlex

Three-dimensional printing is an innovative technology that has gained prominence in recent years due to its attractive features such as affordability, efficiency, and quick production. The technology is used to produce a three-dimensional model by depositing materials in layers using specific printers. In the medical field, it has been increasingly used in various specialties, including neurosurgery, cardiology, and orthopedics, most commonly for the pre-planning of complex surgeries. In addition, it has been applied in therapeutic treatments, patient education, and training wof medical professionals. In the field of obstetrics and gynecology, there is a limited number of studies in which three-dimensional printed models were applied. In this review, we aim to provide an overview of three-dimensional printing applications in the medical field, highlighting the few reported applications in obstetrics and gynecology. We also review all relevant studies and discuss the current challenges and limitations of adopting the technology in routine clinical practice. The technology has the potential to expand for wider applications related to women's health, including patient counseling, surgical training, and medical education.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.313
Teacher spread0.278 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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