Clinical trial NCT04232462: A Multicentric Validation Study on the Accuracy of Artificial Intelligence Assisted System in Clinical Application of Digestive Endoscopy
Official title: A Multicentric Validation Study on the Accuracy of Artificial Intelligence Assisted System in Clinical Application of Digestive Endoscopy
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Gastrointestinal Disease
Endoscopy
Artificial Intelligence
Keywords: Deep Learning
Lead sponsor: Renmin Hospital of Wuhan University
Sponsor class: OTHER
First posted: 2020-01-18
Enrollment: 10000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who meet the admission criteria for endoscopic examination.

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

Detailed description: Endoscopic diagnosis and treatment play an important role in the discovery and treatment of gastrointestinal diseases.With the rapid increase in the number of endoscopies, the workload of endoscopists increases further.The high workload reduces the quality of endoscopy, leading to incomplete coverage and incomplete detection of lesions.With the rapid increase in the number of endoscopies, the workload of endoscopists increases further.The high workload reduces the quality of endoscopy, leading to incomplete coverage and incomplete detection of lesions.Therefore, carrying out deep learning and other artificial intelligence methods has good academic research and practical value for improving the quality of endoscopic diagnosis and treatment.The research and development, testing and functional evaluation of artificial intelligence devices need to use a large number of endoscopic images, and at the same time, the effectiveness and safety of artificial intelligence devices need to be verified in different hospitals and environments.Based on this, our research group intends to collect endoscopic image data from different hospitals for training and validation of the model.

Eligibility criteria: Inclusion Criteria:

1. male or female aged 18 or above;
2. endoscopy and related examinations should be performed to further clarify the characteristics of digestive tract diseases;
3. be able to read, understand and sign the informed consent;
4. 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;

Exclusion Criteria:

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

Primary outcomes:
measure: Accuracy
timeFrame: 2020.1.12-2023.12.31
measure: Sensitivity
timeFrame: 2020.1.12-2023.12.31
measure: Specificity
timeFrame: 2020.1.12-2023.12.31
measure: Positive Predictive Value (PPV)
timeFrame: 2020.1.12-2023.12.31
measure: Negative Predictive Value (NPV)
timeFrame: 2020.1.12-2023.12.31
measure: Receiver Operating Characteristic (ROC) Curve
timeFrame: 2020.1.12-2023.12.31
measure: Area Under the Curve (AUC)
timeFrame: 2020.1.12-2023.12.31
Secondary outcomes:
measure: mean Average Precision (mAP)
timeFrame: 2020.1.12-2023.12.31
measure: Sørensen-Dice coefficient (F1 score)
timeFrame: 2020.1.12-2023.12.31
measure: Recall Rate
timeFrame: 2020.1.12-2023.12.31
measure: Positive Likelihood Ratio
timeFrame: 2020.1.12-2023.12.31
measure: Negative Likelihood Ratio
timeFrame: 2020.1.12-2023.12.31
Other outcomes:
Locations:
city: Wuhan
country: China
facility: Renmin Hospital of Wuhan University
state: Hubei
Study officials:
affiliation: Wuhan University Renmin Hospital
name: Yu Honggang, MD
role: STUDY_DIRECTOR
References: