AI steps into the lab: could computers speed up cancer diagnosis?
NCT ID NCT06827132
First seen Jun 27, 2026 · Last updated Sep 04, 2026 · Updated 2 times
Summary
This study looks at how doctors currently diagnose lung and breast cancer using tissue samples. It will also test whether artificial intelligence (AI) can help analyze these samples faster and more accurately. Researchers will review records from 600 patients to measure diagnosis times, costs, and how well AI agrees with human experts. The goal is to understand if AI can make cancer diagnosis more efficient without replacing the pathologist.
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 successful, this study could help improve and speed up cancer diagnosis by showing how AI tools can assist pathologists.
- What could go wrong
- This is an observational study, not a treatment trial. It only looks back at existing data, so it cannot prove that AI improves patient outcomes.
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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603 people
The number who actually took part.
- Started
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Oct 2025
- Finished
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Mar 2026
- Lead sponsor
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A company
The lead sponsor is a pharmaceutical, biotech, or medical-device company.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Data from samples that meet the following inclusion criterion will be analyzed. • Sample from adult patients (≥ 18 years) with suspected non-small cell lung cancer or invasive breast cancer or ductal carcinoma in situ.
- 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:Sample from adult patients (≥ 18 years) with suspected non-small cell lung cancer or invasive breast cancer or ductal carcinoma in situ. \- Exclusion Criteria: * Samples with the inadequate technical quality of slides (pre-analytics quality) or images, e.g., broken slides, large out-of-focus areas, slides with fixation artefacts. * Samples from cases that were included in the training or technical validation. * Sample taken by fine needle aspiration. * Sample sent for cytological evaluation.
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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.
Contacts and locations
Locations
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Research Site
São Paulo, Brazil
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Research Site
Nairobi, Kenya
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