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PCOS has three subtypes, with 11-oxygenated androgens increasing metabolic risk.

Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.

Machine learning optimized microneedles for hair loss treatment showed better hair regrowth than minoxidil without safety risks.

Machine learning can improve early and accurate detection of PCOS.

Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.

Machine learning identified three unique subtypes of androgen excess in women with PCOS, each with different metabolic risks.

Age, diabetes, and cardiogenic shock at PCI are key factors linked to in-hospital death in STEMI patients with hypertension.

GBP1 is a key target for treating Epstein-Barr virus-related kidney cancer, and finasteride may help.

The new AI software predicts melanoma outcomes more accurately than traditional methods.

The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.

The USA, China, Italy, and Türkiye lead in diverse PRP research, focusing on healing and pain management.

PCOS forum users view lifestyle changes and supplements positively, but have mixed feelings about contraceptive pills.

The model accurately detects alopecia areata with 84.3% accuracy.

The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.

The system effectively detects scalp diseases and classifies hair fall stages with high precision.

The model accurately classifies hair conditions with 97% accuracy.

A new CNN model can detect Alopecia Areata with 98% accuracy.

3D bioprinting shows promise for creating skin substitutes, but standardized methods are needed for clinical use.

The Ewha Medical Journal is now in PubMed, has an AI article editor, and offers Korean reporting guidelines.

New technologies replicate human skin for testing without animals.

AI in alopecia research needs better tools for predicting treatment outcomes and ensuring fairness.

The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.

A new method accurately captures and renders hair color for real and synthetic images.

Machine learning optimized microneedles promote hair regrowth better than minoxidil without safety risks.

Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.

Optimized microneedles promote hair regrowth better than minoxidil without safety risks.

DNAJB9 cfRNA could help diagnose and treat female hair loss.

Hair proteomics could be a promising non-invasive way to identify stress-related disorders.