Non-Invasive Estimation of Hemoglobin Levels in Blood Using Combined Deep Learning Methods
NCT ID: NCT04865224
Last Updated: 2021-04-29
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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COMPLETED
353 participants
OBSERVATIONAL
2020-07-15
2020-12-30
Brief Summary
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In this study, non-invasive hemoglobin level measurement was aimed with a combined DL model created by using nail images with age, height, weight, BMI, and gender information of the volunteers.
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Detailed Description
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Conditions
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Study Design
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OTHER
CROSS_SECTIONAL
Interventions
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hemoglobin estimation
In this method, in which different deep learning models are used together, the age range is intended to be as wide as possible to provide a quick solution with a high accuracy and low error values.
Eligibility Criteria
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Inclusion Criteria
* Individuals should not have any active hand or nail disease.
* Individuals should know their hemoglobin level.
Exclusion Criteria
ALL
Yes
Sponsors
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Karabuk University
OTHER
Responsible Party
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Hakan Yılmaz
Asst. Prof. (Ph.D.)
Locations
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Karabuk University
Karabük, , Turkey (Türkiye)
Countries
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Other Identifiers
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B17EUni-2020-34
Identifier Type: -
Identifier Source: org_study_id
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