A benchmark dataset for early diabetes prediction in Sierra Leone
# Sierra Leone Diabetes Dataset
## 📌 Overview
The **Sierra Leone Diabetes Dataset** is a synthetically generated dataset designed to support research in early diabetes prediction using machine learning techniques, particularly in low-resource healthcare environments.
This dataset was developed to simulate realistic clinical patterns relevant to Sierra Leone and similar contexts, providing a benchmark resource for researchers, students, and practitioners.
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## ⚠️ Important Note
This dataset is **synthetic** and does not contain real patient data. It was generated to reflect plausible medical distributions and relationships observed in diabetes-related studies.
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## 🎯 Objectives
This dataset is intended to:
* Serve as a **benchmark dataset** for machine learning models
* Support **early diabetes prediction research**
* Enable experimentation in **low-resource healthcare settings**
* Facilitate **federated learning and distributed AI research**
* Encourage reproducible and comparable research outcomes
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## 📊 Dataset Information
* **Number of Instances:** 600
* **Number of Features:** 10
* **Target Variable:** Outcome (Diabetes diagnosis)
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## 🧾 Feature Description
| Feature Name | Description |
| ------------------------ | ------------------------------------------------ |
| Sex | Biological sex (0 = Female, 1 = Male) |
| Pregnancies | Number of pregnancies |
| Glucose | Plasma glucose concentration |
| BloodPressure | Diastolic blood pressure (mm Hg) |
| SkinThickness | Triceps skin fold thickness (mm) |
| Insulin | 2-Hour serum insulin (mu U/ml) |
| BMI | Body Mass Index (weight in kg/(height in m)^2) |
| DiabetesPedigreeFunction | Diabetes likelihood based on family history …