Évaluation tridimensionnelle et optimisation du traitement orthopédique de la scoliose idiopathique adolescente
Bibliographic record
Abstract
Adolescent idiopathic scoliosis involves complex tridimensional deformities of the spine, rib cage and pelvis. Moderate curves generally are treated using an orthosis. This paper presents different studies performed over the last fifteen years related to the biomechanical evaluation and optimization of the orthopedic treatment of scoliotic deformities. Patient specific 3D models of the spine, pelvis and rib cage are computed from calibrated radiographs, and are used to calculate 2D and 3D clinical indices. The torso shape is acquired using surface topography. With such internal and external 3D models, the efficacy of the most frequently used orthoses can be analyzed and new treatments can be developed. Pressures generated by a brace on the patient's trunk were measured using a flexible matrix of pressure sensors and displayed over the patient's internal geometry in order to analyze the brace efficacy. Patient specific finite element models have been developed, including the osseo-ligamentous structures as well as the muscles, the neuro-control, trunk growth and its adaptation to the stress. These models were used to analyze the effects of the Boston brace. The electro-myographic activity also was measured to analyze the << active >> correction mechanisms. Adjustment techniques and software are used to help the orthotists with real time feedback when the brace is being fabricated and adjusted to the patient. Residual growth potential is also being added to the computer model to simulate the long term effect of a brace. The improvement of the orthotic treatments of scoliotic deformities is very encouraging. The exploitation of such tools is expected to allow reaching optimal treatment personalized to each patient. double dagger.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".