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--- |
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pretty_name: "Patient Risk Prediction Dataset" |
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language: |
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- en |
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tags: |
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- medical |
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- healthcare |
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- risk-prediction |
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- patient-data |
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- electronic-health-records |
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- disease-prediction |
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license: "mit" |
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task_categories: |
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- text-classification |
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- text-generation |
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- feature-extraction |
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size_categories: |
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- 1K<n<10K |
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--- |
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# 🏥 HealthRisk-1500: Medical Risk Prediction Dataset |
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## 📌 Overview |
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**HealthRisk-1500** is a real-world **patient risk prediction dataset** designed for training **NLP models, LLMs, and healthcare AI systems**. This dataset includes **1,500 unique patient records**, covering a wide range of **symptoms, medical histories, lab reports, and risk levels**. It is ideal for **predictive analytics, medical text processing, and clinical decision support**. |
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## 🔍 Use Cases |
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- **🩺 Disease Risk Prediction:** Train AI models to assess a patient's risk for diseases like **heart disease, diabetes, and Alzheimer's**. |
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- **🧠 Clinical NLP Applications:** Extract meaningful insights from medical data. |
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- **💡 Healthcare Chatbots & Assistants:** Enhance virtual medical assistants with real-world structured patient records. |
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- **📊 Medical Research & AI Development:** Use in academic research for predictive modeling. |
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## 📊 Dataset Structure |
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The dataset consists of **1,500 patient records** with the following key attributes: |
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| Column Name | Description | |
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|---------------------|-----------------------------------------------------------| |
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| **Patient_ID** | Unique identifier for each patient | |
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| **Age** | Patient's age (20-80 years) | |
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| **Gender** | Male / Female | |
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| **Symptoms** | Reported symptoms (e.g., "Chest pain, fatigue") | |
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| **Medical_History** | Past conditions (e.g., Hypertension, Diabetes) | |
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| **Medications** | Prescribed medications | |
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| **Lab_Reports** | Lab test results (e.g., High cholesterol, Normal sugar) | |
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| **Lifestyle** | Health habits (e.g., Smoker, Active, Sedentary) | |
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| **Doctor_Notes** | Short text summaries from doctors | |
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| **Diagnosis** | Predicted disease (e.g., Heart Disease, Diabetes) | |
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| **Risk_Level** | Patient risk classification (Low, Medium, High) | |
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## 🚀 How to Use the Dataset |
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You can load this dataset using **Hugging Face Datasets Library**: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("lvimuth/HealthRisk-1500-Medical-Risk-Prediction") |
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``` |
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### 🔥 Recommended Models for Training |
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- **BERT / BioBERT / ClinicalBERT** (Text classification, medical text processing) |
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- **DeepSeek LLMs** (Medical text summarization and prediction) |
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- **GPT-based models** (Clinical chatbot training) |
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## 📄 Licensing & Attribution |
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- **License:** 📜 CC BY 4.0 *(Attribution required, free for research & commercial use)*. |
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- **Citation:** Please cite this dataset when using it in your research or projects. |
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## 📬 Contact & Contribution |
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Have suggestions or want to contribute? Open a GitHub issue or reach out to me at **lvimuth**. |
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📢 **If you find this dataset useful, please ⭐ star the project on Hugging Face!** |
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