Clinical applications of three‐dimensional printing in otolaryngology–head and neck surgery: A systematic review
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Medical three-dimensional (3D) printing, the fabrication of handheld models from medical images, has the potential to become an integral part of otolaryngology-head and neck surgery (Oto-HNS) with broad impact across its subspecialties. We review the basic principles of this technology and provide a comprehensive summary of reported clinical applications in the field. METHODS: Standard bibliographic databases (MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, Web of Science, and The Cochrane Central Registry for Randomized Trials) were searched from their inception to May 2018 for the terms: "3D printing," "three-dimensional printing," "rapid prototyping," "additive manufacturing," "computer-aided design," "bioprinting," and "biofabrication" in various combinations with the terms: "ptolaryngology," "head and neck surgery," and "otology." Additional articles were identified from the references of retrieved articles. Only studies describing clinical applications of 3D printing were included. RESULTS: Of 5,532 records identified through database searching, 87 articles were included for qualitative synthesis. Widespread implementation of 3D printing in Oto-HNS is still at its infancy. Nonetheless, it is increasingly being utilized across all subspecialties from preoperative planning to design and fabrication of patient-specific implants and surgical guides. An emerging application considered highly valuable is its use as a teaching tool for medical education and surgical training. CONCLUSIONS: As technology and training standards evolve and as healthcare moves toward personalized medicine, 3D printing is emerging as a key technology in patient care in Oto-HNS. Treating physicians and surgeons who wish to stay abreast of these developments will benefit from a fundamental understanding of the principles and applications of this technology. Laryngoscope, 129:2045-2052, 2019.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it