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Github: datasets/clinicaltrials.py

ir_datasets: Clinical Trials

Index
  1. clinicaltrials
  2. clinicaltrials/2017
  3. clinicaltrials/2017/trec-pm-2017
  4. clinicaltrials/2017/trec-pm-2018
  5. clinicaltrials/2019
  6. clinicaltrials/2019/trec-pm-2019

"clinicaltrials"

Clinical trial information from ClinicalTrials.gov. Used for the Clinical Trials subtasks in TREC Precision Medicine.

"clinicaltrials/2017"

A snapshot of ClinicalTrials.gov from April 2017 for use with the clinicaltrials/2017/trec-pm-2017 and clinicaltrials/2017/trec-pm-2018 Clinical Trials subtasks.

docs

Language: en

Document type:
ClinicalTrialsDoc: (namedtuple)
  1. doc_id: str
  2. title: str
  3. condition: str
  4. summary: str
  5. detailed_description: str
  6. eligibility: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017')
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>

"clinicaltrials/2017/trec-pm-2017"

The TREC 2017 Precision Medicine clinical trials subtask.

queries

Language: en

Query type:
TrecPm2017Query: (namedtuple)
  1. query_id: str
  2. disease: str
  3. gene: str
  4. demographic: str
  5. other: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2017')
for query in dataset.queries_iter():
    query # namedtuple<query_id, disease, gene, demographic, other>
docs

Language: en

Document type:
ClinicalTrialsDoc: (namedtuple)
  1. doc_id: str
  2. title: str
  3. condition: str
  4. summary: str
  5. detailed_description: str
  6. eligibility: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2017')
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>
qrels
Query relevance judgment type:
TrecQrel: (namedtuple)
  1. query_id: str
  2. doc_id: str
  3. relevance: int
  4. iteration: str

Relevance levels

Rel.Definition
0not relevant
1possibly relevant
2definitely relevant

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2017')
for qrel in dataset.qrels_iter():
    qrel # namedtuple<query_id, doc_id, relevance, iteration>
Citation
bibtex: @inproceedings{Roberts2017TrecPm, title={Overview of the TREC 2017 Precision Medicine Track}, author={Kirk Roberts and Dina Demner-Fushman and Ellen Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar and Shubham Pant}, booktitle={TREC}, year={2017} }

"clinicaltrials/2017/trec-pm-2018"

The TREC 2018 Precision Medicine clinical trials subtask.

queries

Language: en

Query type:
TrecPmQuery: (namedtuple)
  1. query_id: str
  2. disease: str
  3. gene: str
  4. demographic: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2018')
for query in dataset.queries_iter():
    query # namedtuple<query_id, disease, gene, demographic>
docs

Language: en

Document type:
ClinicalTrialsDoc: (namedtuple)
  1. doc_id: str
  2. title: str
  3. condition: str
  4. summary: str
  5. detailed_description: str
  6. eligibility: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2018')
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>
qrels
Query relevance judgment type:
TrecQrel: (namedtuple)
  1. query_id: str
  2. doc_id: str
  3. relevance: int
  4. iteration: str

Relevance levels

Rel.Definition
0not relevant
1possibly relevant
2definitely relevant

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2017/trec-pm-2018')
for qrel in dataset.qrels_iter():
    qrel # namedtuple<query_id, doc_id, relevance, iteration>
Citation
bibtex: @inproceedings{Roberts2018TrecPm, title={Overview of the TREC 2018 Precision Medicine Track}, author={Kirk Roberts and Dina Demner-Fushman and Ellen Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar}, booktitle={TREC}, year={2018} }

"clinicaltrials/2019"

A snapshot of ClinicalTrials.gov from May 2019 for use with the clinicaltrials/2019/trec-pm-2019 Clinical Trials subtask.

docs

Language: en

Document type:
ClinicalTrialsDoc: (namedtuple)
  1. doc_id: str
  2. title: str
  3. condition: str
  4. summary: str
  5. detailed_description: str
  6. eligibility: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2019')
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>

"clinicaltrials/2019/trec-pm-2019"

The TREC 2019 Precision Medicine clinical trials subtask.

queries

Language: en

Query type:
TrecPmQuery: (namedtuple)
  1. query_id: str
  2. disease: str
  3. gene: str
  4. demographic: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2019/trec-pm-2019')
for query in dataset.queries_iter():
    query # namedtuple<query_id, disease, gene, demographic>
docs

Language: en

Document type:
ClinicalTrialsDoc: (namedtuple)
  1. doc_id: str
  2. title: str
  3. condition: str
  4. summary: str
  5. detailed_description: str
  6. eligibility: str

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2019/trec-pm-2019')
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>
qrels
Query relevance judgment type:
TrecQrel: (namedtuple)
  1. query_id: str
  2. doc_id: str
  3. relevance: int
  4. iteration: str

Relevance levels

Rel.Definition
0not relevant
1possibly relevant
2definitely relevant

Example

import ir_datasets
dataset = ir_datasets.load('clinicaltrials/2019/trec-pm-2019')
for qrel in dataset.qrels_iter():
    qrel # namedtuple<query_id, doc_id, relevance, iteration>
Citation
bibtex: @inproceedings{Roberts2019TrecPm, title={Overview of the TREC 2019 Precision Medicine Track}, author={Kirk Roberts and Dina Demner-Fushman and Ellen Voorhees and William R. Hersh and Steven Bedrick and Alexander J. Lazar and Shubham Pant and Funda Meric-Bernstam}, booktitle={TREC}, year={2019} }