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license: mit
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# DiabetesDeepInsight-CSV

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

- **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

- **`diabetes.csv`**  
  Pima Indians Diabetes Database (8 clinical features + Outcome).

- **`diabetes_data_upload.csv`**  
  Alternate Pima format, ensuring consistency for cross-validation.

- **`diabetes_binary_health_indicators_BRFSS2015.csv`**  
  CDC BRFSS 2015 health survey (binary diabetes flag, demographics, labs).

- **`diabetes_binary_5050split_health_indicators_BRFSS2015.csv`**  
  Balanced 50/50 subset of BRFSS 2015 (equal cases/controls).

- **`diabetes_012_health_indicators_BRFSS2015.csv`**  
  BRFSS 2015 three-class (“No”, “Pre-diabetes”, “Diabetes”) converted to binary.

- **`Retinopathy_Debrecen.csv`**  
  Tabular features from EyePACS retinal exams (0/1 retinopathy → proxy for diabetes).

- **`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

1. **Rich Clinical Indicators**  
   - Age, BMI, blood pressure, insulin, lipid profiles, lifestyle habits (smoking, activity), etc.

2. **Retinopathy-Derived Biomarkers**  
   - Vessel diameter, hemorrhage counts, texture features—ideal for image-to-CSV pipelines.

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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