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
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".