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