AI takes on the experts: a test for diagnosing mycosis fungoides
NCT ID NCT07795242
First seen Aug 31, 2026 · Last updated Sep 01, 2026 · Updated 1 time
Summary
This study asks whether an artificial intelligence algorithm can diagnose mycosis fungoides, a rare type of skin lymphoma, from biopsy slides as accurately as certified dermatopathologists. Researchers will compare the AI's sensitivity and specificity against expert readings using 50 stored slides. If the AI proves reliable, it could support pathologists in diagnosing this challenging condition.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If the AI performs as well as experts, it could offer a faster, more accessible diagnostic tool for mycosis fungoides, potentially helping pathologists in settings with limited specialist access.
- What could go wrong
- This is a small, observational study using stored slides, not a real-world test. The AI may not match expert accuracy, and results may not generalize to other labs or patient populations.
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
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About 50 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Oct 2026
An estimate. Start dates often move.
- Expected to finish
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Dec 2027
An estimate. End dates often move.
- Lead sponsor
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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 MF cases will be collected from the pathology archive of Al hussein dermatopathology unit
- Ages
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Children (under 18), adults (18 to 64) and older adults (65 and over)
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
Show the full entry requirements Hide 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: * Slides will be included in the study if they meet the following criteria: * Histopathological slides diagnosed as MF. * Slides with adequate staining and preservation allowing clear visualization of histopathological features. Exclusion Criteria: * Slides will be excluded if they meet any of the following criteria: * Slides with poor staining quality or significant artifacts interfering with histopathological interpretation. * Slides that were damaged, faded, or inadequately preserved. * Slides 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.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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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
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Faculty of Medicine , Al Azhar university , Nasr city , Cairo , Egypt
Cairo, Egypt
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