TRADITIONAL AND COMPLEMENTARY MEDICINE FREQUENTLY APPLIED IN MUSCULOSKELETAL DISEASES
Bibliographic record
Abstract
Traditional and complementary medicine is not considered as a part of conventional medicine but it is defined as practices and products in various fields of medicine and health care system. Traditional and complementary medicine practices have been increasing all over the world and in our country since the 1990s. According to the World Health Organization 2000 data, the frequency of traditional and complementary medicine is 80% in Africa, 70% in Canada, 48% in Australia, 42% in the US, 38% in Belgium and 49% in France. In our country, due to the low number of studies the frequency of traditional and complementary medical practices was reported to be 42-70%. The Ministry of Health issued the "Regulation on Traditional and Complementary Medicine " in the Official Gazette on 27 October 2014. With this regulation, teaching and application methods of complementary treatment methods and who can apply the treatment subjects were clarified. Treatment authority was given to physicians, and to dentists and pharmacists to practice in the field of their own. Regulations include acupuncture, ozone, mesotherapy, prolotherapy, hypnosis, hirudotherapy, reflexology, homeopathy, phytotherapy, osteopathy, chiropractic, maggot practices, apitherapy, cup and music therapy methods. In our country, most application reasons are musculoskeletal pain and rheumatologic diseases. This is followed by cancer, neurological diseases and chronic diseases. In this review, the most commonly used methods in musculoskeletal system diseases are mentioned. Each physician can choose a different treatment based on his or her approach. However, because of the low quality of scientific studies and insufficient randomized controlled studies, evidence-based suggestions can not be made. Nonetheless, there is a discussion of the effects of traditional and complementary medicine practices on various systems and symptoms, as well as studies on the mechanisms of these effects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".