Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
80 participants
OBSERVATIONAL
2024-09-15
2025-01-31
Brief Summary
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The seemingly long queue for the expensive health screenings has put the high-risk groups, including but not limited to the elderly, in a vulnerable position as they can hardly perform regular and frequent check-ups.
In light of this, our team is determined to research a solution that is conducive to the preventive healthcare of strokes and cardiovascular diseases through one of the newly proposed devices: PyrocksTM Tag Lite.
This study aims to investigate an approach for developing a robust deep learning model for analysing ultrasound images and incorporate the model into our established prototype to perform intima-media thickness measurement and risk assessment.
Main points that the clinical trial can assist in solving the existing problem:
The acquisition procedures are non-invasive, painless, and safe for the participants. Clinical trials \& test data will assist in testing and training our neural network model.
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Detailed Description
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Conditions
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Study Design
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CASE_ONLY
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* Patients with cardiovascular diseases (CVD), including current smokers or diagnosed with diabetes, dyslipidaemia, coronary artery disease, cerebrovascular disease, hypertension, atherosclerotic cardiovascular disease, high blood pressure, high BMI index and those under antihypertensive treatment.
Exclusion Criteria
19 Years
ALL
No
Sponsors
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Chinese University of Hong Kong
OTHER
Responsible Party
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Professor Bryan Ping Yen YAN
professor
Locations
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The Chinese University of Hong Kong
Shatin, , Hong Kong
Countries
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Facility Contacts
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Other Identifiers
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2024.468
Identifier Type: -
Identifier Source: org_study_id
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