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Medical Entrance Exam Question Data
Education & Learning Analytics
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About
This resource is a large-scale collection of Multiple-Choice Question Answering (MCQA) data designed around real-world medical entrance examination content. It is expected to drive further research in the fields of deep learning and Artificial Intelligence for the purpose of enhancing knowledge surrounding healthcare. The data provides a valuable learning tool as it includes careful categorisation of questions, answer choices, the correct response, and detailed explanations for why each option is right or wrong, serving as a powerful diagnostic tool.
Columns
The dataset contains several key features across its files:
- question: The specific medical question being asked.
- opa, opb, opc, opd: The four distinct answer options (A, B, C, or D).
- cop: The correct option corresponding to the question.
- choice_type: Indicates whether the question is a single or multiple answer type.
- exp: The detailed explanation for the question and choices.
- subject_name: The broader medical discipline related to the question.
- topic_name: The specific topic covered by the question.
Distribution
The data is delivered across four CSV files. These files are split to facilitate model building and evaluation:
train.csv contains 80% of the data, while test.csv and validation.csv each contain 10%. A separate evaluation.csv file is included for submitting final results in certain competitions. For instance, the testing subset contains 6,150 individual records.Usage
Ideal applications for this data include developing advanced Natural Language Processing (NLP) models capable of accurately addressing medical questions. It can be used to create AI-driven virtual medical examination simulations for practice and assessment. Furthermore, it is suitable for integration into Intelligent Tutoring Systems (ITSs) to assist students in preparing more effectively for medical entrance exams, and for developing question-answering bots for medical applications.
Coverage
The material is structured around subjects and specific topics relevant to medical entrance exams. The questions are categorised by subject name and topic name. Specific details regarding geographic coverage, exact time range, or demographics are not provided, focusing primarily on the structure of the medical curriculum itself.
License
CC0: Public Domain
Who Can Use It
Intended users include data scientists and developers building machine learning models for healthcare, researchers focused on medical knowledge representation and NLP, and healthcare professionals seeking additional educational resources. It is highly beneficial for students preparing for crucial medical entrance exams.
Dataset Name Suggestions
- MedMCQA Dataset
- Medical Entrance Exam Question Data
- AI Healthcare Knowledge Resource
- Large Medical MCQ Collection
Attributes
Original Data Source: Medical Entrance Exam Question Data
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