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Use of Artificial Intelligence to Assess Severity of Facial Melasma

Evaluation of Artificial Intelligence Algorithm in Predicting Modified Melasma Area and Severity Index (mMASI) Scores in Patients with Facial Melasma - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/03/106943
Enrollment
187
Registered
2026-03-27
Start date
Unknown
Completion date
Unknown
Last updated
2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: L814- Other melanin hyperpigmentation

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil

Sponsors

Datta Meghe Medical College and Shalinitai Meghe Hospital and Research Center Nagpur
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Age more than 18 years Clinically diagnosed facial melasma (epidermal, dermal or mixed) Willingness to participate with informed consent

Exclusion criteria

Exclusion criteria: Presence of any other facial lesion other than melasma Active infections / Active dermatoses interfering with pigmentation scoring Use of depigmenting agents within 1 month Recent facial treatments (e.g., peels, lasers) within 4 weeks Any application of topical medication that can interfere with photography and melasma grading

Design outcomes

Primary

MeasureTime frame
Strength of correlation between AI-predicted modified Melasma Area and Severity Index (mMASI) scores and dermatologist-assigned modified MASI scores in Indian patients with facial melasma.Timepoint: Baseline—

Secondary

MeasureTime frame
Level of agreement between AI-predicted scores & clinician-assigned Melasma Severity Index (MSI) scores.Timepoint: Baseline—

Countries

India

Contacts

Public ContactDr Sudhir Singh

Datta Meghe Medical College and Shalinitai Meghe Hospital

sudhirderm@gmail.com8806187862

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: May 1, 2026