Datasets:

Ramesh10
/

medical-emails-noncase-dataset

tags:
  - classification
  - emails
  - non-case
  - operational
  - pharmacovigilance
  - jsonl
  - ml-intern
dataset_info:
  features:
    - name: instruction
      dtype: string
    - name: output
      dtype: string
  config_name: default

Medical Email Classification Dataset - Non-Case Category

This dataset contains 200 unique synthetic emails classified as Non-Case for pharmaceutical/pharmacovigilance email classification tasks.

Classification Category

Non-Case

A Non-Case is an email that is purely operational, administrative, internal or logistical in nature. It does not involve any drug, medication, medical product, patient, health-related event, safety, quality, or commercial evaluation.

Sub-Types (6 Types)

Login or Access Issues - System access problems, password resets, authentication failures
Application Support Requests - Technical issues with software tools and systems
Training or Onboarding Inquiries - Training sessions, onboarding materials, competency assessments
Scheduling or Operational Coordination - Meeting rescheduling, room bookings, deadline extensions
User Management or Account Setup - Account creation, deactivation, permission changes
Workflow or Process Clarification - Process queries, SLA questions, procedure confirmations

Dataset Format

Each example is in strict JSONL format:

{
  "instruction": "SUBJECT: ...\nBODY:\n...",
  "output": "{\"Classification_of_request\": {\"Classification\": \"Non-Case\", \"Confidence_percentage\": \"95%\"}, \"Analysis\": \"...\"}"
}

Dataset Statistics

Total emails: 200
Number of types: 6 (distributed across all emails)

Quality Requirements Met

Each email body contains sufficient narrative and contextual detail
No compressed keyword-style statements
No simple concatenations of one sentence per label
Realistic contextual detail with timing and context
Paragraph-style composition preferred over telegraphic fragments
All topics woven naturally into the message with realistic transitions
Emails feel like coherent human-written messages
No escape characters in the dataset
Strict numeric normalization (e.g., "3 weeks" not "three weeks")

Generated by ML Intern

This dataset repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.

Try ML Intern: https://smolagents-ml-intern.hf.space
Source code: https://github.com/huggingface/ml-intern

Usage

from datasets import load_dataset

dataset = load_dataset('Ramesh10/medical-emails-noncase-dataset')