license: apache-2.0
language:
- ar
pretty_name: s
task_categories:
- question-answering
- text-classification
- text-generation
- zero-shot-classification
tags:
- medical
size_categories:
- 10K<n<100K
Shifaa Arabic Medical Consultations 🏥📊
Overview 🌍
Shifaa is revolutionizing Arabic medical AI by addressing the critical gap in Arabic medical datasets. Our first contribution is the Shifaa Arabic Medical Consultations dataset, a comprehensive collection of 84,422 real-world medical consultations covering 16 Main Specializations and 585 Hierarchical Diagnoses.
🔍 Why is this dataset important?
- First large-scale Arabic medical dataset for AI applications.
- Highly structured and clean – no missing values, duplicates, or unnecessary columns.
- Hierarchical categorization of medical specialties for better NLP and AI training.
- Detailed responses (273 words on average) provide deep medical insights.
Dataset Details 📑
- Number of consultations:
84,422 - Main Specializations:
16 - Hierarchical Diagnoses:
585 - Average answer length:
273 words - Languages:
Arabic
Data Distribution 📊
The dataset covers a wide range of medical fields, making it suitable for various AI-driven applications such as:
✅ Medical Chatbots 🤖
✅ Predictive Models 🔮
✅ AI-powered Recommendation Systems 🏥
✅ Arabic Medical NLP Research 📖
Data Hierarchy 🌐
Our dataset follows a hierarchical structure to enhance precision and usability. Example for Obstetrics and Gynecology:
Word Cloud 🌟
This word cloud visualizes the most frequently used words in questions and answers related to muscle diseases.
Data Source 🔗
The dataset was collected from the Islam Web website using web-scraping tools.
Preprocessing & Cleaning 🛠️
✔ Removed duplicates and null values
✔ Corrected corrupted data
✔ Standardized hierarchical categories for consistency
✔ Eliminated hidden spaces and excess words
Usage & Applications 🚀
Shifaa Arabic Medical Consultations is designed for AI and NLP applications, making it ideal for:
- Medical Question Answering Systems
- Arabic Medical Chatbots
- AI-powered Medical Assistants
- Healthcare Research & AI-driven Text Analysis
How to Use 📥
Download the dataset from Hugging Face and start building your Arabic medical AI applications!
from datasets import load_dataset
dataset = load_dataset("Ahmed-Selem/Shifaa_Arabic_Medical_Consultations")