This dataset is the converted version of MedQuAD. Some notes about the data:
umls_cui, umls_semantic_types, synonyms columns are separated by | character.GARD, MPlusHerbsSupplements, ADAM, MPlusDrugs] sources (31,034 records) are removed from the original dataset to respect the MedlinePlus copyright.umls): Unified Medical Language Systemcui): Concept Unique IdentifierWe noticed there are minor discrepancies between the question types mentioned in the paper and the question types in the dataset. Here is a list of these discrepancies and how you can map types in the dataset to those in the paper:
| Dataset question type | Paper question type |
|---|---|
| how can i learn more | learn more |
| brand names of combination products | brand names |
| other information | information |
| outlook | prognosis |
| exams and tests | diagnosis (exams and tests) |
| stages | ? |
| precautions | ? |
| interactions with herbs and supplements | interaction with herbs and supplements |
| when to contact a medical professional | contact a medical professional |
| research | research (or clinical trial) |
| interactions with medications | interaction with medications |
| interactions with foods | interaction with food |
If you use MedQuAD, please cite the original paper:
@ARTICLE{BenAbacha-BMC-2019,
author = {Asma {Ben Abacha} and Dina Demner{-}Fushman},
title = {A Question-Entailment Approach to Question Answering},
journal = {{BMC} Bioinform.},
volume = {20},
number = {1},
pages = {511:1--511:23},
year = {2019},
url = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3119-4}
}
This dataset is the converted version of MedQuAD. Some notes about the data:
umls_cui, umls_semantic_types, synonyms columns are separated by | character.GARD, MPlusHerbsSupplements, ADAM, MPlusDrugs] sources (31,034 records) are removed from the original dataset to respect the MedlinePlus copyright.umls): Unified Medical Language Systemcui): Concept Unique IdentifierWe noticed there are minor discrepancies between the question types mentioned in the paper and the question types in the dataset. Here is a list of these discrepancies and how you can map types in the dataset to those in the paper:
| Dataset question type | Paper question type |
|---|---|
| how can i learn more | learn more |
| brand names of combination products | brand names |
| other information | information |
| outlook | prognosis |
| exams and tests | diagnosis (exams and tests) |
| stages | ? |
| precautions | ? |
| interactions with herbs and supplements | interaction with herbs and supplements |
| when to contact a medical professional | contact a medical professional |
| research | research (or clinical trial) |
| interactions with medications | interaction with medications |
| interactions with foods | interaction with food |
If you use MedQuAD, please cite the original paper:
@ARTICLE{BenAbacha-BMC-2019,
author = {Asma {Ben Abacha} and Dina Demner{-}Fushman},
title = {A Question-Entailment Approach to Question Answering},
journal = {{BMC} Bioinform.},
volume = {20},
number = {1},
pages = {511:1--511:23},
year = {2019},
url = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3119-4}
}