Polycystic Ovary Syndrome Herbal Treatments and Medicinal Plants: A Comprehensive Review
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) represents one of the most common endocrine disorders affecting women of reproductive age, serving as a major contributor to infertility on a global scale, with an estimated prevalence varying from 6 to 20% worldwide. PCOS is a complex syndrome defined by hyperandrogenism, irregular ovulation, and the presence of polycystic ovarian morphology. This syndrome is often associated with metabolic complications, including obesity, dyslipidemia, and an elevated risk of insulin resistance and developing type 2 diabetes. Symptoms include menstrual irregularities, weight gain, hirsutism, acne, and infertility. The presently available conventional treatment options for PCOS include hormonal contraceptives, insulin sensitizers, anti-androgens, and ovulation-inducing agents. While these treatments may offer symptomatic relief, they often entail potential side effects and do not adequately address the underlying cause of this syndrome. Herbal remedies have been used for centuries across cultures to manage various disorders due to their cost efficiency, availability, and safe nature. Several studies have demonstrated the efficiency of herbal remedies in the treatment of female reproductive disorders, including PCOS. This review comprises an extensive survey of the latest animal and clinical studies concerning plants and phytochemicals that have demonstrated effectiveness in alleviating symptoms associated with PCOS, as well as treating the underlying mechanisms involved in their efficacy
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".