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The SAAD-41 scale effectively measures the psychosocial impact of alopecia areata.

Certain blood markers, especially MLR, can help diagnose alopecia areata.

Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.

Current corticosteroid pulse therapy is not very effective for severe rapidly progressive alopecia areata.

Diphenylcyclopropenone treatment helps prevent hair loss relapse in alopecia areata patients.

Oral tacrolimus helped a rheumatoid arthritis patient regrow hair lost due to alopecia areata.

New, safer treatments for children's hair disorders are needed, and better evaluation methods are recommended.

Certain gene variations increase the risk of alopecia areata in Koreans.

Patients with alopecia areata should be checked for muscle spasms, diarrhea, and ANA to avoid missing Satoyoshi syndrome.

Mouse models help understand alopecia areata and find treatments.