---
language:
- en
license: apache-2.0
task_categories:
- text-generation
- question-answering
tags:
- health
- english
- kicaulah-ai
- natural-language
- medical
- health
- pediatric
- first-aid
- mental-health
- clinical-qa
- wellness
pretty_name: Kicaulah AI - Dataset Health (Medical QA & Triage)
size_categories:
- 1K<n<10K
---

# Kicaulah AI — Dataset Health (Medical QA & Triage)

## 📖 Description
A high-quality Medical QA and Health Education dataset in natural conversational English. Covers 10 distinct clinical pillars: Pediatrics & Infant Care, Gastric & GERD, Chronic Metabolic Disease (Hypertension, Diabetes, Gout, Cholesterol), Emergency First Aid, Dermatology & Skin Health, Women's Health, Mental Wellness & Sleep Hygiene, Over-The-Counter Pharmacology, Oral & Dental Care, and Respiratory & Infectious Disease. Designed under the Anti-AI-Speak standard with human empathy and zero robotic clichés.

This dataset is strictly curated under the **Anti-AI-Speak Standard**:
- Built using authentic, everyday conversational language.
- Free from generic robotic clichés such as *"As an AI language model..."* or *"That's a great question!"*.
- Prioritizes genuine empathy, real-world context, practical analogies, and natural variations in tone (casual, formal, emotional, concise, and in-depth).

## 🎯 Use Cases
- Fine-tuning Large Language Models (LLMs) for natural, empathetic medical assistant applications.
- Training health triage bots to deliver concise, reassuring, and red-flag-conscious medical guidance.
- Benchmarking conversational healthcare responses against everyday, realistic patient inquiries.

## 📊 Dataset Structure
| Column | Type | Description | Example |
|-------|------|-------------|---------|
| instruction | string | User inquiry or realistic scenario | "My 2-year-old has had a 102F fever for 2 days, what should I do?" |
| response | string | Natural, human, solution-oriented response | "Take a deep breath first. A 102 fever on day 2 is scary..." |
| category | string | Specific domain subcategory | "health" |

## 📈 Statistics
- **Total Examples**: 1,100
- **Train (80%)**: 880
- **Validation (10%)**: 110
- **Test (10%)**: 110

## 🚀 How to Use

```python
from datasets import load_dataset

dataset = load_dataset("Kicaulah/dataset-health")
print(dataset["train"][0])
```

## 📑 Citation
```bibtex
@misc{kicaulah_health,
  title={Kicaulah AI - Dataset Health (Medical QA & Triage)},
  author={Kicaulah AI Team},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/Kicaulah/dataset-health}}
}
```