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Human-AI Uncertainty Callibration for Improved Skin Lesion Segmentation

NCT07468357 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 50

Last updated 2026-03-12

No results posted yet for this study

Summary

The goal of this randomized controlled study is to compare the effect of a new, personalized uncertainty-aware decision model (FDM) to a standard image recognition model in improving the diagnostic accuracy while reducing diagnostic uncertainty in experienced dermatologists tasked with differentiating between melanomas, moles and other benign skin lesions. The main question it aims to answer: Is the FDM a feasible method for an improved human AI partnership in which trust is build, misdiagnoses are avoided, and uncertainty is duly introduced or reduced.

The investigators expect to see only a slight increase in collective diagnostic accuracy for both interventions as the the human participants are skilled dermatologist and thus have high accuracies pre-intervention.

The investigators expect to see a higher increase in diagnostic certainty for the FDM intervention compared to the diagnostic certainty in the Base Model intervention.

The investigators expect to see a higher amount of diagnosis changes from incorrect to correct in the FDM group compared to the Base Model group.

The investigators do not expect any learning effect during the study.

Participants will start by answering a series of training cases consisting of images of skin lesions. These are used to train their individual FDM (only for the FDM-intervention group). From here, the participants will be randomized into two arms determining which of the two interventions they are exposed to. The participants will solve each case withouth any intervention first, and this reply will act as a control.

Conditions

  • Skin Lesions

Interventions

OTHER

Base Model

See arm description.

OTHER

FDM

See arm description

Sponsors & Collaborators

  • Technical University of Denmark

    collaborator OTHER

  • Copenhagen Academy for Medical Education and Simulation

    lead OTHER

Principal Investigators

  • Martin Tolsgaard, Professor · Copenhagen Academy for Medical Education and Simulation

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-01
Primary Completion
2026-07-31
Completion
2026-11-30

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07468357 on ClinicalTrials.gov