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This dataset includes conjunctival and retinal images collected from both diabetic and healthy individuals to support research on diabetes-related vascular changes. For each subject, eight conjunctival images (four per eye: looking left, right, up, and down) are provided. Subjects with diabetes additionally have corresponding left and right retinal fundus images. Metadata for diabetic participants includes classification into subgroups: diabetes only, diabetes with retinopathy, or diabetes with related complications such as hypertension.
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data have 16 features with 1 target value
Scope: Primarily focused on diabetes-related information.
Data Size: Contains a substantial volume of records.
Variables: Likely includes patient demographics, medical history, lab results, medications, treatments, and outcomes.
Temporal Range: Time span covered by the dataset may vary.
Privacy Measures: Anonymized to protect patient identities.
Ethical Considerations: Collected and shared adhering to ethical guidelines.
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This diabetes dataset was collected from 2000 people at the Frankfurt Hospital, Germany. There are eight features in the dataset. Among the 2000 samples, 684 people are Diabetes patients and the rest of them are normal. This dataset is available in the Kaggle repository. The eight features are given below.
i. Pregnancies: To express the Number of pregnancies
ii. Glucose: To express the Glucose level in blood
iii. BloodPressure: To express the Blood pressure measurement
iv. SkinThickness: To express the thickness of the skin
v.
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The data has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital in Sylhet, Bangladesh and approved by a doctor.
This dataset is available in UCI Machine Learning Repository.
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