Ramesh10/medical-emails-company-products-dataset
Medical Emails Classification Dataset - Company Products This dataset contains 800 synthetic medical emails for multi-label classification involving company products. Categories (200 emails each) # Classification String Products Involved 1 Medical Information Product A + Product B 2 Product Complaint Product A + Product B 3 Adverse Event, Product Complaint AE on Product A + PC on Product A + PC on Product B 4 Medical Information, Adverse Event… See the full description on the dataset page: https://huggingface.co/datasets/Ramesh10/medical-emails-company-products-dataset.
Medical Emails Classification Dataset - Company Products
This dataset contains 800 synthetic medical emails for multi-label classification involving company products.
Categories (200 emails each)
Product Naming
- Product A, Product B, Product C: Company products - used exclusively for company-related classifications
- Non-Company Product X: Uses real-world drug names from the approved list: Metformin, Atorvastatin, Amoxicillin, Ibuprofen, Omeprazole, Lisinopril, Levothyroxine, Amlodipine, Methotrexate
Format
Strict JSONL with 2 fields per line:
instruction: Email subject and body (structured as "SUBJECT: ...\nBODY:\n...")output: JSON string containing classification result and analysis
Dataset Characteristics
- Total emails: 800 (all unique)
- No unicode escape characters: No
\u2013or similar escapes - No parenthesis in analysis text
- Numeric normalization: All numbers written as digits
- Mixed senders: HCPs and non-HCPs
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Usage
from datasets import load_dataset
dataset = load_dataset('Ramesh10/medical-emails-company-products-dataset')