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

Conditions

• Diagnostic Accuracy
• Differential Diagnosis

Eligibility Criteria

Sex

ALL

Age

18 Years - N/A

Healthy Volunteers

Accepted

Interventions

• AI Diagnostic System (AIMD.1) — DIAGNOSTIC_TEST
  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.

Study Details

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.

Key Dates

Start date

Mar 19, 2026

Status verified

Mar 2026

Primary completion

Sep 19, 2026

Completion

Sep 19, 2026

Study Design

Enrollment

30 participants (estimated)

Arms

• Arm: Clinician Participants
  Licensed clinicians who participate in diagnostic evaluation tasks using de-identified medical images and semi-synthetic patient simulations to assess diagnostic accuracy. Clinicians provide differential diagnoses for benchmark comparison with an AI diagnostic system.

Primary Outcome Measure

Top-1 Diagnostic Accuracy [ Time Frame: At completion of diagnostic evaluations (up to 6 months) ]

Central Contacts

• Luis R Soenksen, MSE, PhD
  (617) 936-9293
  [email protected]
• Sean Geiger, B.S.
  (412) 412-8786
  [email protected]

Locations (1)

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