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AutoDx-DR Prospective Clinical Validation Study Protocol

NCT04627272 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1539

Last updated 2020-11-13

No results posted yet for this study

Summary

In this study, we will prospectively evaluate the accuracy of a deep-learning based software algorithm in the detection of diabetic retinopathy from 60° wide single-field retinal fundus images.

Conditions

Interventions

DEVICE

AutoDX-DR

AutoDx-DR provides basic image interpretation for the detection of DR and diabetic macular edema (DME) and a Refer or Not Refer recommendation.

Sponsors & Collaborators

  • Rho, Inc.

    collaborator INDUSTRY

  • ClinEdge

    collaborator INDUSTRY

  • Hill-Rom

    lead INDUSTRY

Principal Investigators

  • Antonio Piñero-Piloña, MD · Diabetes Care Center

  • Joseph Woolley, MD · Southwest Internal Medicine

  • Keila Hoover, MD · Hoover Family Medicine

  • Quang Vo, MD · Dr. Steven Barag, DO

  • Peter Mattar, MD · Dr. Peter N. Mattar, MD

  • Efrain Soto, MD · Park Lakes Family Medicine

  • Harish Thakkar, MD · Southwest Medical Clinic

  • Luis Gonzalez-Orozco, MD · Clinic of Luis Gonzalez

  • Jennifer Bellucci-Jackson, MD · Family Medicine Specialists

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
22 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-12-01
Primary Completion
2021-07-31
Completion
2021-07-31
FDA Device
Yes

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Entities

Diseases

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 NCT04627272 on ClinicalTrials.gov