Actively Recruiting

Phase Not Applicable
Age: 18Years +
All Genders
Healthy Volunteers
NCT04332783

Isolating and Mitigating Sequentially Dependent Perceptual Errors in Clinical Visual Search

Led by University of California, Berkeley · Updated on 2026-02-03

10120

Participants Needed

1

Research Sites

708 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

Remote-store-and-forward teledermatology has recently grown exponentially in popularity and use as an efficient, accurate, and cost-effective way to improve the health and well-being of countless patients. Despite advances in machine learning and computer vision, the screening and reading of dermatological images still depends on the visual system of human observers (e.g., clinicians), who receive extensive training to best recognize lesions and anomalies. In remote store-and-forward teledermatology settings, clinicians may examine hundreds of images on a daily basis, seeing several images one after the other. A main underlying assumption of their work is that clinician percepts and decisions about a current image are completely independent from prior viewings. However, we and other groups demonstrated that the visual system has visual serial dependencies (VSDs) at many levels, from perception to decision making, including in clinical tasks. These sequential dependencies, replicated hundreds of times in the literature, mean that what was seen in the past influences (and captures) what is seen and reported at this moment. Theoretically, VSDs are helpful in an autocorrelated natural world, but they are suboptimal in visual tasks conducted in artificial situations where images are not always related. Importantly, serial dependencies in perceptual processing could thus produce significant errors during diagnostic judgments of dermatological images. Our central hypothesis is that VSD can have a disruptive effect in asynchronous remote-store-and-forward teledermatology judgments that impairs accurate detection and recognition of lesions. This hypothesis is supported by our robust pilot data, which show that VSD strongly biases lesion classification in both untrained observers and expert clinicians. The rationale for the proposed research projects is that once it is known how serial dependence arises and how it impacts judgments, we can understand how to control for it. Hence, accuracy of lesion detection and diagnosis can significantly improve. The specific objectives of this proposal are to establish (Aim 1), identify (Aim 2) and mitigate (Aim 3) the impact of VSD on remote-store-and-forward dermatological judgments.

CONDITIONS

Official Title

Isolating and Mitigating Sequentially Dependent Perceptual Errors in Clinical Visual Search

Who Can Participate

Age: 18Years +
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Subjects must have normal or corrected to normal vision with contacts or glasses.
Not Eligible

You will not qualify if you...

  • Subjects must be 18 years or older to participate.
  • Subjects may not participate if they are blind.

AI-Screening

AI-Powered Screening

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Trial Site Locations

Total: 1 location

1

University of California, Berkeley

Berkeley, California, United States, 94720

Actively Recruiting

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Research Team

K

Katrina Wolters, BA

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

DOUBLE

Allocation

RANDOMIZED

Model

SINGLE_GROUP

Primary Purpose

BASIC_SCIENCE

Number of Arms

2

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