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Recruiting Not applicable Interventional Accepts healthy volunteers

Isolating and Mitigating Sequentially Dependent Perceptual Errors in Clinical Visual Search

ClinicalTrials.gov ID: NCT04332783

Public ClinicalTrials.gov record NCT04332783. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.

ClinicalTrials.gov public records Last synced Sep 7, 2026, 6:43 AM EDT

Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.

Brief summary

Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.

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.

Study identification

NCT ID
NCT04332783
Recruitment status
Recruiting
Study type
Interventional
Phase
Not applicable
Enrollment
10,120 participants

Conditions and interventions

Eligibility (public fields only)

Age range
18 Years and older
Sex
All
Healthy volunteers
Accepts healthy volunteers

This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.

Study timeline

Start date
Mar 31, 2019
Primary completion
Jun 29, 2031
Completion
Oct 29, 2032
Last update posted
Feb 2, 2026

2019 – 2032

United States locations

U.S. sites
1
U.S. states
1
U.S. cities
1
Facility City State ZIP Site status
University of California, Berkeley Berkeley California 94720 Recruiting

Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.

About this trial record page

What this page shows
Public field values for ClinicalTrials.gov record NCT04332783, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
What this page does not do
No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
Where the data comes from
Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
Last refresh
Last update posted Feb 2, 2026 · Synced Sep 7, 2026

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Open the official record

The complete protocol, eligibility criteria, and contact information for NCT04332783 live on ClinicalTrials.gov.

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