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Stigmatization and quality of life in people with alopecia are influenced by gender and sociodemographics, suggesting a need for better support.

STK11 gene polymorphism does not predict metformin response in PCOS.

High levels of Anti-Müllerian Hormone (AMH) in the blood can strongly predict Polycystic Ovarian Syndrome (PCOS) and related issues in women of reproductive age.

A new score can help predict which patients might have trouble urinating after prostate surgery.

Certain medications and smaller pupil size increase the risk of intraoperative floppy iris syndrome during eye surgery.

Both atopy and eosinophilia are linked to more severe hair loss in people with alopecia areata.

Lower SHBG levels may increase the risk of PCOS.

Machine learning can effectively predict type 2 diabetes risk.

The study identified 12 potential biomarkers for hair loss and how they affect hair growth.

Ischemic modified albumin could be a new indicator of oxidative stress in people with alopecia areata.

The neighborhood face index (NFI) accurately predicts properties of complex molecules.

Ultrasound measurement of the ovarian stroma to total area ratio is not a reliable single predictor of high male hormone levels in Thai women with PCOS, but works better when combined with clinical signs.

A gene-based model predicts lung adenocarcinoma outcomes and helps guide treatment decisions.

Lower zinc levels may predict less effective hair loss treatment.

Machine learning can accurately predict mental disorders.

Desmopressin-loaded liposomes can effectively deliver drugs through the skin, improving bioavailability and patient compliance.

The study initially suggested a genetic link between thyroid issues and hair loss.

Tadalafil and Finasteride may help treat aggressive melanoma.

DiZyme accurately predicts nanozyme activities to aid in discovering new applications.

AVT is highly conserved and may have antimicrobial properties.

Loneliness reduces academic enthusiasm in students.

The new skin model can predict how chemicals might cause skin allergies.

DNA phenotyping can predict physical traits like eye, hair, and skin color, improving forensic investigations.

Adding obesity data to machine learning models improves heart disease prediction accuracy.

N6-methyladenosine affects hair follicle development differently in Rex and Hycole rabbits.

Cialis and Finasteride could be repurposed to treat aggressive melanoma.

A deep learning model accurately predicts male hair loss types using scalp images.

Low PON1 levels may indicate and predict the severity of hair loss.