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Artificial Intelligence-aimed Point-of-care Ultrasound Image Interpretation System

NCT04876157 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 300

Last updated 2025-09-19

No results posted yet for this study

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.

Conditions

  • Ultrasound Image Interpretation

Interventions

DIAGNOSTIC_TEST

Artificial intelligence-aimed point-of-care ultrasound image interpretation system

improve the sensitivity and specificity of the AI-aimed ultrasound interpretation system

Sponsors & Collaborators

  • National Taiwan University Hospital

    lead OTHER

Principal Investigators

  • Wan-Ching Lien · National Taiwan University Hospital

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-08-01
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04876157 on ClinicalTrials.gov