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- license: mit
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+ ---
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+ license: mit
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+ ---
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+
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+ # DiabetesDeepInsight-CSV
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+ A comprehensive, multi-source CSV collection for Type 2 Diabetes prediction, combining clinical indicators and retinopathy features. Ideal for researchers and practitioners in medical AI and data science.
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+ ---
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+
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+ ## 🚀 Highlights
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+ - **Multi-Dataset Fusion**: Integrates Pima Indians, BRFSS surveys, and Retinopathy Debrecen—over 300,000 records in total.
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+ - **Clinical & Retinopathy Features**: Blood tests, demographics, lifestyle factors, and retinal image–derived biomarkers.
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+ - **Balanced & Stratified**: Includes 50/50 splits, three-class→binary conversions, and curated train/test splits.
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+ - **Plug‐and‐Play CSVs**: Ready for immediate ingestion with popular ML frameworks (scikit-learn, XGBoost, PyTorch).
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+ ---
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+ ## 📂 Included Files
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+ - **`diabetes.csv`**
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+ Pima Indians Diabetes Database (8 clinical features + Outcome).
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+ - **`diabetes_data_upload.csv`**
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+ Alternate Pima format, ensuring consistency for cross-validation.
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+ - **`diabetes_binary_health_indicators_BRFSS2015.csv`**
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+ CDC BRFSS 2015 health survey (binary diabetes flag, demographics, labs).
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+ - **`diabetes_binary_5050split_health_indicators_BRFSS2015.csv`**
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+ Balanced 50/50 subset of BRFSS 2015 (equal cases/controls).
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+ - **`diabetes_012_health_indicators_BRFSS2015.csv`**
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+ BRFSS 2015 three-class (“No”, “Pre-diabetes”, “Diabetes”) converted to binary.
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+ - **`Retinopathy_Debrecen.csv`**
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+ Tabular features from EyePACS retinal exams (0/1 retinopathy → proxy for diabetes).
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+ - **`diabetic_data.csv`**
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+ (Optional) 130-US Hospitals clinical records—can be extended for readmission or ICD-9-based diabetes flags.
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+ ---
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+
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+ ## ✨ Key Features
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+ 1. **Rich Clinical Indicators**
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+ - Age, BMI, blood pressure, insulin, lipid profiles, lifestyle habits (smoking, activity), etc.
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+ 2. **Retinopathy-Derived Biomarkers**
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+ - Vessel diameter, hemorrhage counts, texture features—ideal for image-to-CSV pipelines.
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+ 3. **Preprocessed & Label-Aligned**
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+ - Unified `Outcome` column (0 = No Diabetes, 1 = Type 2 Diabetes) across all CSVs.
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+ ---
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+ Unlock deeper insights and achieve >95% accuracy with integrated clinical & retinopathy features! 🎉
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+ ```
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+ ```