ChiCTR2300078073
尚未开始
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2023-11-28
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anaemia and HbA1c
機器學習方法確定視網膜特徵以進行全血細胞計數 (包括血紅素) 及糖化血紅素的研究
機器學習方法確定視網膜特徵以進行全血細胞計數 (包括血紅素) 及糖化血紅素的研究
Primary 1. To identify specific retinal image characteristics that significantly associated with completed blood picture (including anemia) and HbA1c using machine-learning method. 2. Determine a classification model for completed blood picture including anemia and HbA1c based on a machine-learning approach as well as from specific set of retinal characteristics. Secondary 1. To validate the classification model using a separate data set of retinal images.
横断面
探索性研究/预试验
N/A
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the Chinese University of Hong Kong
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300
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2023-12-01
2024-11-30
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-Age>18 -Willing to sign the inform consent -Willing to comply with procedures required in the protocol -Completed a CBP and HbA1c blood tests；
请登录查看-Poor retinal images quality that cannot be used in the analysis -Subjects with other eye diseases which are not suitable for retinal imaging, such as severe cataract, glaucoma, atretopsia, corneal plague. -Subjects are distress with flashlight or have experience with photosensitive seizure. -Unwillingness or inability to comply with procedures required in the protocol；
请登录查看Centre for Clinical Research and Biostatistics, CUHK
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