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The Seoul International Dermatology Symposium was a successful event that highlighted new dermatology treatments and fostered international relations.

In Japan, sex reassignment surgery for gender identity disorder faces challenges and needs better medical support and education.

Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.

Certain genetic markers may increase or decrease prostate cancer risk.

The Spanish HSS-29 scale effectively measures changes in life quality due to female-pattern hair loss.

Certain medications, hypertension, and short eye length increase the risk of Intraoperative Floppy Iris Syndrome during cataract surgery.

The Rotterdam Study investigates diseases in older adults and has produced many research findings.

Clinicians and researchers must stay informed about big data to improve dermatology care.

During COVID-19, Iraqi women saw more hair loss and skin issues like acne due to stress, masks, and hygiene habits.

The study concludes that the new clinical scoring system is a quick, low-cost, and accurate method for diagnosing COVID-19.

Infrared spectral imaging can map hair growth proteins and sugars without staining.

The meeting showcased rare skin disease cases, highlighting the need for accurate diagnosis and treatment.

Scalp hair characteristics vary across different regions of India and can help identify a person's origin.

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Certain genetic variations in IGF2BP2 and IGFBP3 are linked to a higher risk of PCOS.

Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.

The model accurately identifies hair diseases using deep learning.

In 2020, a new online survey was made to help identify Polycystic ovary syndrome (PCOS) in women, but it needs some improvements for better understanding and accuracy.

Irisin and betatrophin levels change differently in PCOS, which may help assess metabolic risks.

The workshop promoted better medicine use and health practices through global collaboration.

The method accurately detects diabetes with 94% effectiveness, reducing misdiagnosis risk.

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The new method predicts post-hair transplant images more accurately than other methods.