Harnessing Artificial Intelligence for Diagnosing Androgenetic Alopecia: A Training and Validatio… (NCT07294313) | Clinical Trial Compass
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Harnessing Artificial Intelligence for Diagnosing Androgenetic Alopecia: A Training and Validation Study
Egypt400 participantsStarted 2026-04-25
Plain-language summary
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).
Who can participate
Age range12 Years – 50 Years
SexALL
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for the patient group:
Inclusion criteria:
* 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).