# Bioethics of syndrome diagnosis using 3D image analysis

> **NIH NIH U01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $152,200

## Abstract

Project Summary/Abstract
This supplement will address the unintended consequences and collateral damage that arise when facial
recognition software is used for medical purposes, such as for syndrome diagnosis as in our Facebase-funded
project. In Aim 1, we will determine whether the accuracy of this technology varies based on self-reported race,
sex and age. In this aim, we examine our existing database for evidence of bias based on self-reported race,
sex or age. We further determine the extent to which these variables influence classification performance. To
the extent sample sizes allow, we will carry this analysis to the level of specific syndromes. Finally, we will use
anonymized reference datasets of non-syndromic faces to compare false positive rates based on NIH race
definitions, sex and age. The outcome of this aim is to objectively establish bias and estimate the effects of
under-representation across race, age and sex categories within our data. In Aim 2, we will determine how the
reports of race-, sex- and age-based bias in facial recognition technology may influence views of the
technology and its application amongst researchers and clinicians. This aim will establish the extent to which
the storing of large databases of facial images and the application of machine learning processes to them for
diagnostic purposes may raise privacy concerns. The concerns investigated will include potential hacks into
protected health information; fear relating to the bias in some facial recognition software (and, potentially, in
the Facebase database); and fear of discrimination in the application of the technology, such as by insurers.
The outcome will be a white paper that targets a high-profile journal, summarizing the findings and defining
crucial issues that should guide the development of facial imaging for disease diagnosis and clinical usage.

## Key facts

- **NIH application ID:** 10132648
- **Project number:** 3U01DE028729-02S1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Yang Chai
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $152,200
- **Award type:** 3
- **Project period:** 2019-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10132648

## Citation

> US National Institutes of Health, RePORTER application 10132648, Bioethics of syndrome diagnosis using 3D image analysis (3U01DE028729-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10132648. Licensed CC0.

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