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IDEAS-AAP System Diagnoses Acute Abdominal Pain

NCT05497258 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 151

Last updated 2022-11-08

No results posted yet for this study

Summary

This is a study to validate the effect of the intelligent diagnostic evidence-based analytic system in acute abdominal pain augmentation. Included physicians were randomly assigned into control or AI-assisted group. In this experiment, the whole electronic health record of each acute abdominal pain patient was divided into two parts, signs and symptoms recording (including chief complaint, present history, physical examination, past medical history, trauma surgery history, personal history, family history, obstetrical history, menstrual history, blood transfusion history, drug allergy history) and auxiliary examination recording (including laboratory examination and radiology report). For each case, the control group readers will first read the signs and symptoms recording of electronic health record and make a clinical diagnosis. Then the readers have to decide to either order a list of auxiliary examinations or confirm the clinical diagnosis without further examination. If the readers choose to order examinations, the corresponding examination results will be feedback to the readers, and the readers can then decide to either continue to order a list of auxiliary examinations or make a confirming diagnosis. Such cycle will last until the reader make a confirming diagnosis. For the AI-assisted readers, the physicians were additionally provided with the feature extracted by IDEAS-AAP, a list of suspicious diagnoses predicted by IDEAS-AAP, and corresponding diagnostic criteria according to guidelines. After the readers get the examination results, the IDEAS-AAP will renew its diagnosis prediction

Conditions

  • Artificial Intelligence
  • Diagnoses Disease

Interventions

DEVICE

Artificial intelligence assistant system

The AI-assisted diagnosis system can provide the direction of disease diagnosis in real time and assist the doctor to give the final diagnosis

Sponsors & Collaborators

  • Renmin Hospital of Wuhan University

    lead OTHER

Principal Investigators

  • Honggang Yu, MD · Renmin Hospital of Wuhan University

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-08-15
Primary Completion
2022-09-01
Completion
2022-10-01

Countries

  • China

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 NCT05497258 on ClinicalTrials.gov