AI-Assisted Acute Myeloid Leukemia Evaluation With the Leukemia End-to-End Analysis Platform (LEAP) Versus Clinician-Only Assessment

Completed · Not applicable

Conditions studied: Acute Promyelocytic Leukemia (APL), Acute Myeloid Leukaemia (AML)

In brief

This study will test whether artificial intelligence (AI) can help doctors diagnose a rare blood cancer called acute promyelocytic leukemia (APL) more quickly and accurately. Doctors usually examine bone marrow samples under a microscope to make this diagnosis, but it can be challenging and time-consuming. In this study, doctors will review bone marrow samples under three different conditions: * Unaided Review: Without AI assistance. * AI as Double-Check: AI-generated evaluation shown after the doctor makes an initial decision. * AI as First Look: AI-generated evaluation shown at the start of the review. Doctors will be randomly assigned to different orders of these three conditions. This design will allow us to compare how AI support affects diagnostic accuracy, speed, and confidence.

Key facts

Study ID
NCT07203885
Run by
Harvard Medical School (HMS and HSDM)
People needed
10
Starts
2025-09-09
Expected to finish
2025-10-10
Last updated by the study team
2025-10-31

Who can join

Age: any. Sex: any. Healthy volunteers: not accepted.

Where it is running

Full record on ClinicalTrials.gov

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