Patient doctor Dataset
Mental Health & Wellness
Related Searches
Trusted By




"No reviews yet"
Free
About
This dataset contains medical queries and responses related to gastrointestinal and reproductive health, specifically focusing on abdominal pain, ulcers, hormonal treatments, and related concerns. It includes detailed patient descriptions, their symptoms, and corresponding professional advice given by healthcare providers. The dataset is ideal for analysing medical consultation patterns and exploring healthcare response effectiveness.
Dataset Features:
- PD_ID: Unique identifier for each query and response.
- Description: Brief summary of the patient's query or concern.
- Patient: The patient's detailed description of symptoms or situation.
- Doctor: The doctor's response to the patient's query, including treatment suggestions.
- Problem Description: Full text of the patient's inquiry or issue.
Usage:
This dataset can be used to:
- Develop and test predictive models for healthcare consultations.
- Analyze common symptoms, treatments, and medical advice for gastrointestinal and reproductive conditions.
- Identify patterns in patient concerns related to digestive and menstrual health.
- Train natural language processing (NLP) models to automatically respond to medical queries or provide advice.
Coverage:
The dataset covers various gastrointestinal issues, hormonal treatments, and reproductive health concerns, making it relevant for modelling and analyzing healthcare interactions, medical decision-making, and the effectiveness of various treatments.
License:
CC0 (Public Domain)
Who can use it:
This dataset is designed for data scientists, machine learning practitioners, healthcare researchers, and medical students interested in healthcare predictive analytics.
How to use it:
- Develop predictive models for medical consultations.
- Conduct feature analysis or compare different algorithms for healthcare problem diagnosis.
- Investigate correlations between symptoms, treatments, and outcomes.
- Analyze the language used in healthcare communications and the relevance of doctor responses to patient symptoms.