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AI takes on the microscope: a new test for skin cancer diagnosis

NCT ID NCT07786376

Diagnosis Sponsor: Al-Azhar University Source: ClinicalTrials.gov ↗

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 26, 2026 · Last updated Aug 27, 2026 · Updated 1 time

Summary

This study asks whether an artificial intelligence algorithm can accurately identify basal cell carcinoma, a common type of skin cancer, from digitized tissue samples. Researchers will compare the AI's diagnostic performance—its sensitivity and specificity—against the assessments of certified dermatopathologists. The study will use 50 histopathological slides that have been confirmed as BCC and are well-preserved, excluding any with poor staining or damage. The goal is to see if AI could serve as a reliable tool in the diagnostic process.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
An artificial intelligence algorithm that analyzes digitized tissue samples to identify basal cell carcinoma
What this could lead to
If successful, this could pave the way for AI-assisted pathology, potentially speeding up skin cancer diagnosis and reducing the workload on specialists.
What could go wrong
The study is small and early, and AI performance on a limited set of slides may not reflect real-world accuracy. Poor-quality or unusual samples could also trip up the algorithm.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 50 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Oct 2026

An estimate. Start dates often move.

Expected to finish

Dec 2027

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

H\&E stained glass slides of bcc cases will be collected from the pathology archive of Al-hussein dermatopathology unit .

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Histopathological slides diagnosed as BCC. * Slides with adequate staining and preservation allowing clear visualization of dermatopathological features. Exclusion Criteria: * Slides with poor staining quality or significant artifacts interfering with histopathological interpretation. * Slides that were damaged, faded, or inadequately preserved. * Cases with uncertain or inconclusive original diagnoses. * Slides that could not be successfully digitized due to technical limitations ex very short or too long slides.

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Conditions

The condition(s) this trial relates to.

basal cell carcinoma basal cell neoplasm

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Basal cell cancer

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Al hussein universty hospital

    Cairo, Nasr City, Egypt

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