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Not yet recruiting NCT07468357

Human-AI Uncertainty Callibration for Improved Skin Lesion Segmentation

No phase Interventional Skin Lesions

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Base Model, FDM.
Who it may be relevant to
Registry conditions: Skin Lesions. Basic parameters: No limits · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Center list to be confirmed — check the primary protocol.
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

The Effect of Human-AI Uncertainty Calibration vs. AI Uncertainty Alone on the Diagnostic Accuracy of Human Experts for Skin Lesions - a Randomized Controlled Trial.

Overview

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.

Detailed description

A detailed description of the FDM is presented in the references.

Interventions

  • Other Base Model
    See arm description.
  • Other FDM
    See arm description

Primary outcome measures

  • Accuracy [Time frame: Immediately after the intervention.]
Secondary outcome measures (2)
  • Uncertainty [Time frame: Immediately after the intervention.]
  • Cut-off uncertainty [Time frame: Immediately after the intervention.]

Eligibility criteria

Inclusion criteria

  • Board certified dermatologists with clinical experience in dermoscopic diagnosis.

Exclusion criteria

  • Doctors who have not yet finished their specialization and dermatologists.
  • Dermatologists without clinical experience in dermoscopic diagnosis.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Diagnostic

Study locations

Center list to be confirmed — check the primary protocol.

Publications

  • Kampen, P.J.T. et al. (2026). Uncertainty-Aware Classification: A Human-Guided Bayesian Deep Learning Framework. In: Sudre, C.H., et al. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging. UNSURE 2025. Lecture Notes in Computer Science, vol 16166. Springer, Cham. https://doi.org/10.1007/978-3-032-06593-3_19

Identifiers

NCT: NCT07468357 · F-25076782

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗