AI tool aims to catch hidden hepatitis c and HIV in ERs

NCT ID NCT07406490

Not yet recruiting Diagnosis Sponsor: University of Florida Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study will test a new computer tool that helps emergency doctors spot patients at high risk for hepatitis C and HIV. The tool uses a machine learning algorithm to analyze patient data and pops up an alert for the doctor. Researchers will compare this targeted screening with universal screening and standard care to see which finds more undiagnosed cases. About 6,466 adults aged 18-79 will take part.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: machine learning algorithm-based screening tool
What this could lead to: If successful, this tool could help emergency departments identify more people with undiagnosed hepatitis C and HIV, leading to earlier treatment.
What could go wrong: This is an observational study, not a treatment trial. The tool may not work as well in other hospitals or may not significantly increase diagnosis rates.

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Conditions

The condition(s) this trial relates to.

AIDS Emergencies hepatitis C virus infection HIV infectious disease Infections

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

HEPATITIS C VIRUS (HCV) HEPATITIS C VIRUS (HCV) INFECTION HIV (HUMAN IMMUNODEFICIENCY VIRUS)

Contacts and locations

Locations

UF Health Jacksonville Emergency Room

Jacksonville, Florida, 32209, United States
UF Health North Emergency Room

Jacksonville, Florida, 32218, United States
UF Health Shands Emergency Room / Trauma Center

Gainesville, Florida, 32608, United States

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