Artificial Intelligence-aimed Point-of-care Ultrasound Image Interpretation System
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Ultrasound is a non-invasive and non-radiated diagnostic tool in the emergency and critical care settings. In clinical practice, timely interpretation of sonographic images to facilitate decision-making is essential. However, it depends on operators' experience. As usual, it takes time for junior emergency physicians to have good diagnostic accuracy through traditional sonographic education. How to shorten the learning This proposal is for an one-year project. In this project, we aim to investigate the feasibility of using AI for sonographic image interpretation. The main project is responsible for coordination between the two sub-projects and the main project, providing image resources, and using U-Net (Convolutional Networks for Biomedical Image Segmentation) and Transfer Learning to build up the models for image recognition and validating the efficacy of the models. The purpose of Subproject 1 is to develop an image recognition system for dynamic images: pericardial effusion. After building up the model, validating the efficacy and future revision will be done. Subproject 2 comes out an image recognition system for static images: hydronephrosis. After building up the model, validating the efficacy and future revision will be done.
This pioneer study can provide two AI-assisted ultrasound image recognition systems in the real clinical conditions. They can experience of clinical applications and contribute to current medical education. Moreover, it can improve decision-making process and quality of care in the emergency and critical care units. Furthermore, the set-up models can be used in other target ultrasound image recognition in the future.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Wan-Ching Lien, Ph D
- Phone Number: +886-2-23123456
- Email: wanchinglien@ntu.edu.tw
Study Contact Backup
- Name: Wan-Ching Lien
- Phone Number: 0988088719
- Email: dtemer17@yahoo.com.tw
Study Locations
-
-
None Selected
-
Taipei, None Selected, Taiwan, 100
- Recruiting
- Wan-Ching Lien
-
Contact:
- Wan-Ching Lien
- Phone Number: +886223123456
- Email: wanchinglien@ntu.edu.tw
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- patients receiving echocardiography or renal ultrasound
Exclusion Criteria:
- patients not receiving echocardiography or renal ultrasound
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Artificial intelligence-aimed ultrasound image interpretation
|
improve the sensitivity and specificity of the AI-aimed ultrasound interpretation system
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
sensitivity and specificity of AI interpretation
Time Frame: 6 months
|
increase the sensitivity and specificity of AI to interpret the ultrasound image
|
6 months
|
Collaborators and Investigators
Investigators
- Principal Investigator: Wan-Ching Lien, National Taiwan University Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- 202006124RINC
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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