Tele-orthopaedics: A systematic mapping study
Bibliographic record
Abstract
INTRODUCTION: The use of telemedicine in orthopaedics can provide high-quality orthopaedic services to patients in remote areas. Tele-orthopaedics is widely acknowledged for decreasing travel, time and cost, increasing accessibility and quality of care. In the absence of a comprehensive review on tele-orthopaedics applications and services, here, we systematically identify and classify the tele-orthopaedic applications and services, and provide an overview of the trends in the field. METHODS: In this study, a systematic mapping was conducted to answer six research questions, we searched the databases Scopus, PubMed, IEEE Digital Library and Web of Science up to 2019. Consequently, 77 papers were screened and selected on the basis of specific inclusion and exclusion criteria. RESULTS: We found that mobile-based teleconsultation was mostly asynchronous, while non-mobile teleconsultation was synchronous. The results showed that the physician-patient relationship was more common than other interactions, such as physician-physician and physician-robot interactions. In addition, more than half of the services provided by tele-orthopaedics have been used for orthopaedic diseases/traumas in which joint replacement and fracture reduction have been the most important orthopaedic procedures. It has been noted that more attention has been paid to tele-orthopaedics in developed countries such as the USA, Australia, Canada and Finland. DISCUSSION: Telemonitoring (teleconsultation and telemetry) and telesurgery (telerobotics and telementoring) were found to be the two major forms of tele-orthopaedics. Mobile phones were used asynchronously in most of the teleconsultations. The development of different applications may result in the use of multiple smartphones applications in real-time teleconsultation. The use of smartphones is expected to increase in the near future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".