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AutoMated BUrn Diagnostic System for Healthcare (AMBUSH)

NCT05167461 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2023-10-23

No results posted yet for this study

Summary

The primary objective of this study is to develop a high accuracy and automated system that can provide early assessment of burn injuries with at least 90% accuracy in absence of burn experts, using AI and FDA cleared harmonic ultrasound TDI data based on the analysis of mechanical and hemodynamic properties of the subcutaneous burned tissue. Data collected in this study will lead to the development of better diagnostic tools that could inform clinical burn practices by enabling doctors to determine burn depth and the need for surgery with greater speed and accuracy, resulting in better clinical outcomes.

Conditions

  • Burns Multiple
  • Burns
  • Thermal Burn
  • Burn Infection

Interventions

OTHER

Collection of imaging by ultrasonography

The investigators will collect burn image data to be processed through the software combined with the deep machine learning to find automated diagnostic burn assessment with accuracy of \>95% compared to human assessment

Sponsors & Collaborators

  • Eskenazi Health

    collaborator OTHER

  • Indiana University

    lead OTHER

Principal Investigators

  • Gayle Gordillo, MD · Indiana University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-05-24
Primary Completion
2023-05-25
Completion
2023-05-25

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05167461 on ClinicalTrials.gov