Published April 9, 2025 | Version v3

A Targeted Dataset for AI-Enhanced Diabetes Care Communication

Authors/Creators

Contributors

Data collector:

  • 1. Universiti Kuala Lumpur

Description

This dataset contains anonymized doctor-patient consultation records collected from a widely used online telemedicine platform in China. It is specifically curated for natural language processing (NLP) applications in the healthcare domain, particularly focusing on diabetes-related medical dialogues.

The dataset has been carefully segmented, translated, and organized into two main components:

1. original_txt.zip

  • Contains 19 individual .txt files named part_1.txt through part_19.txt.

  • Each file includes 1,000 real-world consultation threads in Chinese, with structured multi-turn dialogues between patients and doctors.

  • All entries follow a consistent format, segmented by markers such as id=xxx, to facilitate automated parsing and processing.

  • Personally identifiable information (PII) has been strictly removed to ensure privacy.

2. translated_txt.zip

  • Contains the English-translated versions of each corresponding file in original_txt.zip, following a one-to-one mapping (part_1_english.txt, part_2_english.txt, etc.).

  • Translation was performed using Google Translate (via googletrans library), preserving the original structure, labeling, and dialogue format for each entry.

  • These English versions enable broader accessibility and cross-linguistic research.

Files

original_txt.zip

Files (15.7 MB)

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md5:68dfc90555d77a00e9302b2a225b1baf
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