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Low SHBG and high FAI, FT, and DHEAS levels are effective in identifying PCOS.

PSA levels are higher in women with PCOS, but FAI is a more accurate marker for diagnosis.

New models predict male pattern baldness better than old ones but still need improvement.

Finger length ratios don't predict baldness in men.

Free Testosterone Index, bioavailable testosterone, and androstenedione are the most accurate for diagnosing excess male hormones in PCOS.

Women with nonclassic 21-hydroxylase deficiency can have successful pregnancies through IVF, with certain factors affecting their chances.

Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.

Low HDL-C, uric acid, and 25-hydroxyvitamin D are risk factors for early-onset male hair loss.

Women with PCOS have different levels of certain fats and proteins in their blood, which could help diagnose the condition.

Young HS patients often have other physical and mental health issues, and research on HS covers a wide range of topics including genetics, triggers, treatments, and the need for more data.

A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.

No single biomarker is reliable enough for diagnosing and assessing SLE.

Androgenic alopecia in men is mainly linked to family history, hormonal imbalances, and metabolic issues, but can also be influenced by lifestyle habits, environmental factors, and deficiencies in certain vitamins and microelements like copper.

About 2.2% of women with symptoms of high male hormones have a mild form of congenital adrenal hyperplasia, and measuring a specific hormone level can accurately diagnose it.

Researchers found a white halo around hair in most patients with a specific type of hair loss, which helps in early diagnosis and treatment.

Genetic data can predict male-pattern baldness with moderate accuracy, especially for early-onset cases in some European men.

Different levels of anti-Müllerian hormone can help diagnose polycystic ovary syndrome in women of different ages.

Hair microRNAs could be effective biomarkers for diagnosing scleroderma.

Most patients with Porphyria Cutanea Tarda had skin blisters and were often affected by hepatitis C and alcohol abuse, with differences between familial and sporadic cases.

Herbal compounds like ricinoleic acid, quercetin-3-O-rutinoside, and hinokiflavone may be safe and effective for treating hair loss.

Measuring the distance from the anus to the clitoris may moderately help diagnose polycystic ovary syndrome, especially in certain cases.

AMH is a good marker for diagnosing PCOS, but global standards are needed.

Anti-Müllerian hormone is a specific marker for ovarian issues in women with conditions like PCOS.

Women with persistent acne and high levels of antimullerian hormone are more likely to have polycystic ovarian syndrome.

AMH levels are higher in women with PCOS and can indicate the number of small follicles in their ovaries.

Researchers found four genes that could help diagnose severe alopecia areata early.

Certain gene variations increase male hair loss risk, influenced by hormone levels.

The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.

The document suggests new ways to assess and diagnose hyperandrogenism to improve accuracy.

Four genes are potential markers for hair loss condition alopecia areata, linked to a specific type of cell death.