Artificial Intelligence Clinical Trial
Official title:
A Single-center, Prospective, Parallel Randomized Controlled Study Evaluating the Clinical Effectiveness of an Intelligent Graphic Report System for Upper Gastrointestinal Endoscopy
The objective of this study is to assess the effectiveness of an AI-based reporting system for upper gastrointestinal endoscopy. The primary question that this study aims to address is whether the reporting system can enhance the completeness and accuracy of endoscopic reports when assisted by AI, as drafted by endoscopists. Patients will be randomly assigned to either the experimental group or the control group. In the experimental group, physicians will draft EGD reports with the assistance of the AI-based reporting system, while in the control group, physicians will use the conventional reporting system to draft EGD reports. At the same time, the AI-based reporting system will automatically generate a report of the EGD examination.
Status | Not yet recruiting |
Enrollment | 125 |
Est. completion date | May 20, 2024 |
Est. primary completion date | April 20, 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: 1. Aged 18 years 2. Aim to undergo screening, surveillance, and diagnosis 3. Undergo sedated EGD 4. Able to read, understand, and sign informed consent Exclusion Criteria: 1. EGD contraindications 2. Not suitable for sedated endoscopy after anaesthesia evaluation 3. Biopsy contraindications 4. Active upper gastrointestinal bleeding or emergency oesophagogastroduodenoscopy (EGD) 5. Pregnancy 6. Upper gastrointestinal surgery or residual stomach 7. Not suitable for recruitment after investigator evaluation because of other high-risk conditions |
Country | Name | City | State |
---|---|---|---|
n/a |
Lead Sponsor | Collaborator |
---|---|
Renmin Hospital of Wuhan University |
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Completeness of reporting lesions | Calculation method = number of report lesions / total number of lesions x 100% | one month | |
Secondary | Completeness of report drafting on lesion features | Calculation method = number of drafted features of lesions / total number of features required to be drafted x 100% | one month | |
Secondary | Accuracy of report drafting on lesion features | Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100% | one month | |
Secondary | Reporting time | The time that endoscopists draft reports | one month | |
Secondary | Completeness of reporting lesions of AI system | Calculation method = number of report lesions / total number of lesions x 100% | one month | |
Secondary | Accuracy of report drafting on lesion features of AI system | Calculation method = number of accurately drafted features of lesions / total number of drafted features x 100% | one month | |
Secondary | Physician satisfaction survey | Use 5-point Likert scale to assess physician satisfaction, acceptance, and trust in using the intelligent graphic report system to draft endoscopic reports. | one month |
Status | Clinical Trial | Phase | |
---|---|---|---|
Completed |
NCT04589078 -
Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
|
||
Completed |
NCT03857438 -
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
|
||
Completed |
NCT04735055 -
Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
|
||
Not yet recruiting |
NCT05452993 -
Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography
|
N/A | |
Not yet recruiting |
NCT04337229 -
Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques
|
N/A | |
Completed |
NCT05687318 -
A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment
|
N/A | |
Recruiting |
NCT06051682 -
Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.
|
N/A | |
Not yet recruiting |
NCT06039917 -
Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions
|
N/A | |
Not yet recruiting |
NCT06362629 -
AI App for Management of Atopic Dermatitis
|
N/A | |
Recruiting |
NCT06059378 -
Real-life Implementation of an AI-based Optical Diagnosis
|
N/A | |
Recruiting |
NCT06164002 -
A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials
|
N/A | |
Completed |
NCT05517889 -
Repeatability and Stability of Healthy Skin Features on OCT
|
||
Completed |
NCT05006092 -
Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)
|
N/A | |
Completed |
NCT04816981 -
AI-EBUS-Elastography for LN Staging
|
N/A | |
Recruiting |
NCT04535466 -
Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
|
||
Enrolling by invitation |
NCT04719117 -
Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
|
||
Completed |
NCT04399590 -
Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
|
||
Recruiting |
NCT04126265 -
Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps
|
N/A | |
Recruiting |
NCT06255808 -
Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
|
||
Recruiting |
NCT04131530 -
Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence
|