metadata
language:
- it
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: opa
dtype: string
- name: opb
dtype: string
- name: opc
dtype: string
- name: opd
dtype: string
- name: cop
dtype:
class_label:
names:
'0': a
'1': b
'2': c
'3': d
- name: choice_type
dtype: string
- name: exp
dtype: string
- name: subject_name
dtype: string
- name: topic_name
dtype: string
splits:
- name: test
num_bytes: 1510301
num_examples: 6150
- name: validation
num_bytes: 2469102
num_examples: 4183
- name: train
num_bytes: 143781256
num_examples: 182822
download_size: 94116148
dataset_size: 147760659
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: validation
path: data/validation-*
- split: train
path: data/train-*
task_categories:
- question-answering
tags:
- medical
pretty_name: MedMCQA-ITA
size_categories:
- 100K<n<1M
MedMCQA-ITA is the Italian version, automatically translated, of a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.
The MedMCQA task can be formulated as X = {Q, O} where Q represents the questions in the text, O represents the candidate options, multiple candidate answers are given for each question O = {O_1, O_2, ..., O_n}. The goal is to select the single or multiple answers from the option set.
Original dataset can be found here.
Related paper: https://arxiv.org/abs/2407.06011