Harnessing Artificial Intelligence for Diagnosing Androgenetic Alopecia: A Training and Validation Study

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Conditions studied: Androgenetic Alopecia

In brief

The aim of this study is to develop and validate deep learning models in diagnosis of male and female pattern hair loss, and assessment of its severity based on clinical and trichoscopic image by handheld dermoscopy and administrative data (age and sex).

Key facts

Study ID

NCT07294313

Run by

Cairo University

People needed

400

Starts

2026-04-25

Expected to finish

2026-11-25

Last updated by the study team

2026-03-20

Who can join

Age: 12 and older, up to 50. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Patients with male or female pattern hair loss diagnosed clinically or suspected clinically and confirmed trichoscopically
• Age of disease onset 12-50 years old
• Both genders
• Any grade of androgenetic alopecia
• Any duration of androgenetic alopecia
• Any skin type
• Exclusion criteria by clinical and trichoscopic examination:
• Patients with patchy hair loss or Telogen effluvium only.
• Patients with cicatricial alopecia or diffuse alopecia areata
• Patients with inflammatory scalp disorders (psoriasis, seborrheic dermatitis, lichen planopilaris and frontal fibrosing alopecia in a pattern distribution)
• Lack of patient cooperation.
• for the control group: apparently healthy participants not suffering from the following: AGA, patchy hair loss, cicatricial alopecia, diffuse alopecia areata, inflammatory scalp disorders (psoriasis, seborrheic dermatitis, lichen planopilaris and frontal fibrosing alopecia in a pattern distribution).

Where it is running

• Faculty of Medicine Cairo University — Cairo, Cairo Governorate, Egypt

Full record on ClinicalTrials.gov

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