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Evaluation of One-Shot Vision Differential Diagnosis (OSVDE) and Multi-Step Conversational Non-Inferiority (MSCNE) in AI Medical Interviewing

NCT07470463 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 30

Last updated 2026-03-25

No results posted yet for this study

Summary

This study evaluates the diagnostic performance of a multimodal artificial intelligence (AI) system (AIMD.1) using de-identified medical images and semi-synthetic patient simulations. The study combines retrospective analysis of existing publicly available image datasets with prospective data collection from licensed clinicians who complete diagnostic evaluation tasks.

In the One-Shot Vision Differential Evaluation (OSVDE) stage, clinicians review individual de-identified medical images and generate a ranked list of potential diagnoses based solely on visual features. In the Multi-Step Conversational Non-Inferiority Evaluation (MSCNE) stage, clinicians complete diagnostic assessments using semi-synthetic patient simulations derived from de-identified medical images. Clinician performance will be compared with the AI system on the same diagnostic tasks.

Human participants consist solely of licensed clinicians who provide diagnostic responses. Medical images and simulated cases are study materials and are not considered study participants. No identifiable patient data are used, and the AI system is evaluated in an offline research environment and is not used for clinical decision-making or patient care.

Conditions

  • Differential Diagnosis
  • Diagnostic Accuracy

Interventions

DIAGNOSTIC_TEST

AI Diagnostic System (AIMD.1)

AIMD.1 (also known as NollaMD agent) is a multimodal artificial intelligence (AI) diagnostic system designed to generate differential diagnoses based on analysis of medical images and structured clinical information. In this study, the system is evaluated using de-identified medical images and semi-synthetic patient simulations under controlled research conditions. The AI system generates ranked diagnostic outputs and associated confidence scores, which are compared with reference diagnoses and clinician performance metrics. The system is evaluated in an offline research environment. AI outputs are not used for clinical decision-making, patient management, or real-world medical care.

Sponsors & Collaborators

  • Magic Health Inc. (d.b.a. Nolla Health)

    lead INDUSTRY

Principal Investigators

  • Luis R Soenksen, MSE, PhD · Nolla Health

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-03-19
Primary Completion
2026-09-19
Completion
2026-09-19

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 NCT07470463 on ClinicalTrials.gov