Atopic Dermatitis: Conventional and Integrative Medicine
Bibliographic record
Abstract
Although Western medicine and ideas about atopic dermatitis (AD) have become popular in many Asian countries, local beliefs about the disease and its treatment often prevail. The multi- racial background of these countries as well as the influence of the diverse religions (such as Taoism and Ramadan) in these regions often lead to diverse belief systems about the causes of AD (such as the Chi concept, also known as the balance of yin and yang) and the types of treatment (e.g. herbal remedies, topical versus concoctions, and decoctions). In addition, many of the cultural practices are preserved among the Southeast Asian minorities residing in the United Kingdom and North America. Eastern treatments typically take a holistic approach to AD and emphasize the psychosomatic component of the disorder. This overview provides a summary of the difference between conventional, complementary, alternative, and integrative medicine in terms of epidemiology, aetiology, therapy, and prognosis in children with AD. There are a number of similarities in genetic and environmental factors in epidemiology and aetiology; however, differences exist in terms of the concept of management. Complementary and alternative medicine, traditional Chinese medicine, and integrative medicine usage are not only prevalent among the Asian population but are also becoming more popular and accepted in Western societies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".