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Artificial Intelligence-aimed Point-of-care Ultrasound Image Interpretation System
Sponsor: National Taiwan University Hospital
Summary
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.
Key Details
Gender
All
Age Range
20 Years - Any
Study Type
INTERVENTIONAL
Enrollment
300
Start Date
2020-08-01
Completion Date
2026-12-31
Last Updated
2025-09-19
Healthy Volunteers
No
Conditions
Interventions
Artificial intelligence-aimed point-of-care ultrasound image interpretation system
improve the sensitivity and specificity of the AI-aimed ultrasound interpretation system
Locations (1)
Wan-Ching Lien
Taipei, None Selected, Taiwan