Breast Cancer AI Imaging Study

This study aims to develop a social health platform called MammoChat (https://MammoChat.com) that allows patients to share their real-world patient data to a trusted network for development of clinical intelligence to improve patient outcomes. Therefore:

1. The investigator will establish a Discourse social network where patients can anonymously and securely share their breast imaging and interact with other patients. 2. The investigator will use standardized questionnaires to understand the impact of use of the social network on outcomes related to breast cancer screening such as anxiety. 3. The investigator will assemble a crowdsourced, de-identified radiographic repository for training, testing, and validating AI models aimed at earlier and more accurate disease detection for breast cancer.

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Key information

Conditions

Breast Cancer Breast Cancer Screening Breast Diseases Breast Neoplasms Neoplasms Neoplasms by Site Skin Diseases Skin and Connective Tissue Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University of Central Florida

Orlando, Florida, 32827, United States

About this study

With over 40,000,000 mammograms run annually in the US, there are psychological consequences of breast cancer imaging that are well documented among patients such as stress and anxiety from largely false positive or indeterminant readings by radiologists.

This UCF MammoChat platform is one of the first projects that engages patients to donate their breast cancer imaging in an effort to reduce the psychological consequences of breast cancer imaging using social networks and artificial intelligence.

This repository will be supported and maintained by the University of Central Florida College of Medicine (UCF COM) Clinical and Aerospace Research team. These clinical research coordinators will operate the repository, including administering patients, imaging sites and transfers through an administrative panel.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Adults, ages 18 and older
Had a radiographic breast cancer imaging test, either for screening or diagnosis of breast cancer, with either positive or negative results performed in a US institution.
Have an email account with access to a reliable internet connection or smartphone

Exclusion criteria

Minors , ages under 18
Prisoners. Given the repository design, prisoners are unlikely to participate and provide a consent
Adults who are unable to provide consent.

Treatment and study plan

Primary outcomes

AI Model Development

Time frame: 25 years

Train, test and validate AI models with de-identified radiographic images collected from participants.
Psychological Impact of Breast Cancer Screening

Time frame: 25 years

Assess user anxiety using the standardized COS-BC (Consequences of Screening in Breast Cancer) questionnaire.
Social Discourse for Patients on Wellness Network

Time frame: 25 years

Assess patient participation on Discourse social network using standardized user metrics such as activity logs, images posted, other interactions, etc.

Sponsors and collaborators

Lead sponsor

University of Central Florida

Other

Registry information

Official study title

Elucidating the Impact of Social Wellness and Artificial Intelligence on the Psychological Consequences of Breast Cancer Imaging

Important dates

Study start: 2024
Primary completion: 2025
Study completion: 2025
First posted: Sep 19, 2024
Registry last updated: Sep 12, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

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