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Patient Inquiry and Physician Answer Data
Data Science and Analytics
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About
A powerful collection of medical questions and expert responses specifically tailored for natural language processing applications. It includes more than 43,000 real-life patient inquiries, which are systematically sorted into 31 distinct categories. The resource is invaluable for developing systems that analyze correlations between treatments, medical protocols, and chronic diseases. Responses are provided by a variety of healthcare professionals, including physicians, nurses, and pharmacists, ensuring a robust array of domain expertise.
Columns
The core data file,
train.csv, contains three main fields:- qtype: Defines the specific category or type of medical question (e.g., symptoms, information).
- Question: The textual query posed by the patient regarding a health condition or protocol.
- Answer: The expert, detailed response provided by a healthcare professional.
Distribution
The data is structured as a single primary file in CSV format (
train.csv), approximately 22.47 MB in size. It comprises three columns detailing the question type, the question, and the corresponding answer. The set contains thousands of validated records, providing a large base for analysis and model training.Usage
This data is exceptionally useful for various applications, including:
- Developing advanced medical diagnostic tools utilizing Natural Language Processing (NLP) techniques.
- Creating machine learning models to anticipate and suggest treatment options for diverse medical conditions.
- Building virtual assistants and chatbots capable of accurately answering a broad spectrum of user questions about healthcare protocols.
- Analyzing patient search patterns to gain insights into commonly queried treatments or chronic conditions.
Coverage
The content is based on patient inquiries reflecting real-life medical situations. Specific geographic or time frame details related to the data collection are not detailed in the available documentation.
License
CC0: Public Domain
Who Can Use It
- NLP Engineers: For training and fine-tuning language models on specialised medical terminology and dialogue structures.
- Data Scientists: To execute complex queries and build predictive models related to health outcomes and protocols.
- Medical Researchers: To explore correlations and patterns across patient inquiries and expert recommendations.
- AI Developers: For creating robust, accurate conversational AI for the healthcare sector.
Dataset Name Suggestions
- Healthcare NLP Training Set
- Expert Medical Q&A Corpus
- Patient Inquiry and Physician Answer Data
- Structured Health Dialogue Database
Attributes
Original Data Source: Patient Inquiry and Physician Answer Data
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