A Multicentric Validation Study on the Accuracy of Artificial Intelligence Assisted System in Clinical Application of Digestive Endoscopy

NCT04232462 | Unknown

• 1 other identifier: EA-19-006
• Study Type: observational
• Target: 10,000
• Locations: 1 country
• Sites: 1

Brief Summary

This is an artificial intelligence-based optical artificial intelligence assisted system that can assist endoscopists in improving the quality of endoscopy.

Conditions

Gastrointestinal Disease; Endoscopy; Artificial Intelligence

Keywords

Deep Learning

Outcome Measures

Primary Outcomes (7)

• Accuracy

  Calculate the accuracy of AI's judgment on images and videos. Accuracy is :

  2020.1.12-2023.12.31

• Sensitivity

  Calculate the sensitivity of AI's judgment on images and videos. Sensitivity is : in the sample that is positive actually, the proportion that judges to be positive (for example, in the person that is really sick, be judged to be the proportion that is sick by the hospital), computation way is the ratio that true positive divides true positive add false negative (be positive actually, but judge is negative).

  2020.1.12-2023.12.31

• Specificity

  Calculate the specificity of AI's judgment on images and videos. Specificity is : in the samples that are actually negative, the proportion of those that are judged negative (for example, the proportion of those who are not actually ill, who are judged by the hospital to be not ill) is calculated as the ratio of true negative divided by true negative + false positive (actually negative, but judged positive).

  2020.1.12-2023.12.31

• Positive Predictive Value (PPV)

  The percentage of true positive people in positive test results indicates the probability that the positive test results belong to true cases.

  2020.1.12-2023.12.31

• Negative Predictive Value (NPV)

  The percentage of true negative to negative test results indicates the probability that the negative test results are non-cases.

  2020.1.12-2023.12.31

• Receiver Operating Characteristic (ROC) Curve

  Definition 1:The subject's operating characteristic curve is a coordinate graph composed of false positive rate as the horizontal axis and true positive rate as the vertical axis, and the curve drawn by the subject under specific stimulus conditions due to the different judgment criteria. Definition 2:ROC curves were created by plotting the proportion of true positive cases (sensitivity) against the proportion of false positive cases (1-specificity), by varying the predictive probability threshold.

  2020.1.12-2023.12.31

• Area Under the Curve (AUC)

  Calculate the area under the curve of AI's receiver operating characteristic (ROC) curve.

  2020.1.12-2023.12.31

Secondary Outcomes (5)

• mean Average Precision (mAP)

  2020.1.12-2023.12.31

• Sørensen-Dice coefficient (F1 score)

  2020.1.12-2023.12.31

• Recall Rate

  2020.1.12-2023.12.31

• Positive Likelihood Ratio

  2020.1.12-2023.12.31

• Negative Likelihood Ratio

  2020.1.12-2023.12.31

Interventions

Endoscopists refer to AI for diagnosis DIAGNOSTIC_TEST

The AI will provide a clinical diagnosis during endoscopy.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who meet the admission criteria for endoscopic examination.

You may qualify if:

• male or female aged 18 or above;
• endoscopy and related examinations should be performed to further clarify the characteristics of digestive tract diseases;
• be able to read, understand and sign the informed consent;
• the researcher believes that the subject can understand the process of the clinical study, is willing and able to complete all the study procedures and follow-up visits, and cooperate with the study procedures;

You may not qualify if:

• have participated in other clinical trials, signed the informed consent and have been in the follow-up period of other clinical trials;
• drug or alcohol abuse or psychological disorder in the last 5 years;
• pregnant or nursing women;
• subjects with previous history of gastrointestinal surgery;
• the researcher considers that the subject is not suitable for endoscopy and related examination;
• high-risk diseases or other special conditions that the investigator considers inappropriate for the subject to participate in the clinical trial.

Sponsors & Collaborators

• Renmin Hospital of Wuhan University: lead

Study Sites (1)

Renmin Hospital of Wuhan University

Wuhan, Hubei, 430000, China

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

endoscopy images and videos

MeSH Terms

Conditions

Gastrointestinal Diseases

Interventions

Diagnosis

Condition Hierarchy (Ancestors)

Digestive System Diseases

Study Officials

• Yu Honggang, MD

  Wuhan University Renmin Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 14, 2020
• First Posted: January 18, 2020
• Study Start: January 1, 2020
• Primary Completion: December 31, 2025
• Study Completion: December 31, 2025
• Last Updated: January 8, 2021

Record last verified: 2021-01

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)