CONTEMPORARY AND FUTURE DEVELOPMENT OF 3D PRINTING TECHNOLOGY IN THE FIELD OF ASSISTIVE TECHNOLOGY, ORTHOTICS AND PROSTHETICS
Bibliographic record
Abstract
3D printing is considered as a helpful technology that facilitates innovative assistive technology, orthotics, and prosthetics development. This technology could likely contribute to positive treatment outcomes. It could also mitigate the challenges encountered when using the traditional methods. Our team’s research in the application of 3D printing in prosthetics, orthotics and biomedical technology has shown beneficial results in its use. This article gives a general description on application of CAD/CAM, digitalization and 3d printing in this industry followed by short description of two spinal-related projects conducted in our research team. Technological and clinical challenges on utilization of this technology have been listed. Finally, this manuscript provides recommendation for broader applications and developments of the aforementioned technology through interdisciplinary practices. A glimpse into the future of 3D printing in the healthcare industry shows that this industry is poised to continue having a significant impact in this sector. It should be emphasized that assistive technology, orthotics, and prosthetics require a human touch and connection, and no digital tool or technology can replace such requirements. Indeed, multi-disciplinary collaboration is the key to the success of applications of 3D printing. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/42225/32491 How To Cite: Hassan Beygi B, Wong M.S. Contemporary and future development of 3D printing technology in the field of assistive technology, orthotics and prosthetics. Canadian Prosthetics & Orthotics Journal. 2023; Volume 6, Issue 2, No.10. https://doi.org/10.33137/cpoj.v6i2.42225 Corresponding Author: M.S. WONG, PhDThe Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong.E-Mail: m.s.wong@polyu.edu.hkORCID ID: https://orcid.org/0000-0002-4157-9528
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".