Clinical Trials - ir

`"clinicaltrials"`

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

TREC Precision Medicine website

`"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.

Dataset information

docs Metadata

241K docs

Language: en

Document type:

ClinicalTrialsDoc: (namedtuple)

doc_id: str
title: str
condition: str
summary: str
detailed_description: str
eligibility: str

Examples:

Python API CLI PyTerrier

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>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2017 docs



[doc_id]    [title]    [condition]    [summary]    [detailed_description]    [eligibility]
...

You can find more details about the CLI here.

{
  "docs": {
    "count": 241006,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  }
}

`"clinicaltrials/2017/trec-pm-2017"`

The TREC 2017 Precision Medicine clinical trials subtask.

queries docs qrels Citation Metadata

30 queries

Language: en

Query type:

TrecPm2017Query: (namedtuple)

query_id: str
disease: str
gene: str
demographic: str
other: str

Examples:

Python API CLI PyTerrier

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>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2017/trec-pm-2017 queries



[query_id]    [disease]    [gene]    [demographic]    [other]
...

You can find more details about the CLI here.

Rel.	Definition	Count	%
0	not relevant	`12K`	91.0%
1	possibly relevant	`735`	5.6%
2	definitely relevant	`436`	3.3%

{
  "docs": {
    "count": 241006,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  },
  "queries": {
    "count": 30
  },
  "qrels": {
    "count": 13019,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "0": 11848,
          "1": 735,
          "2": 436
        }
      }
    }
  }
}

`"clinicaltrials/2017/trec-pm-2018"`

The TREC 2018 Precision Medicine clinical trials subtask.

queries docs qrels Citation Metadata

50 queries

Language: en

Query type:

TrecPmQuery: (namedtuple)

query_id: str
disease: str
gene: str
demographic: str

Examples:

Python API CLI PyTerrier

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>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2017/trec-pm-2018 queries



[query_id]    [disease]    [gene]    [demographic]
...

You can find more details about the CLI here.

Rel.	Definition	Count	%
0	not relevant	`12K`	85.6%
1	possibly relevant	`1.2K`	8.3%
2	definitely relevant	`873`	6.2%

{
  "docs": {
    "count": 241006,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  },
  "queries": {
    "count": 50
  },
  "qrels": {
    "count": 14188,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "0": 12141,
          "2": 873,
          "1": 1174
        }
      }
    }
  }
}

`"clinicaltrials/2019"`

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

Dataset information

docs Metadata

306K docs

Language: en

Document type:

ClinicalTrialsDoc: (namedtuple)

doc_id: str
title: str
condition: str
summary: str
detailed_description: str
eligibility: str

Examples:

Python API CLI PyTerrier

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>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2019 docs



[doc_id]    [title]    [condition]    [summary]    [detailed_description]    [eligibility]
...

You can find more details about the CLI here.

{
  "docs": {
    "count": 306238,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  }
}

`"clinicaltrials/2019/trec-pm-2019"`

The TREC 2019 Precision Medicine clinical trials subtask.

queries docs qrels Citation Metadata

40 queries

Language: en

Query type:

TrecPmQuery: (namedtuple)

query_id: str
disease: str
gene: str
demographic: str

Examples:

Python API CLI PyTerrier

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>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2019/trec-pm-2019 queries



[query_id]    [disease]    [gene]    [demographic]
...

You can find more details about the CLI here.

Rel.	Definition	Count	%
0	not relevant	`11K`	83.2%
1	possibly relevant	`1.7K`	13.1%
2	definitely relevant	`485`	3.7%

{
  "docs": {
    "count": 306238,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  },
  "queries": {
    "count": 40
  },
  "qrels": {
    "count": 12996,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "0": 10811,
          "1": 1700,
          "2": 485
        }
      }
    }
  }
}

`"clinicaltrials/2021"`

A snapshot of ClinicalTrials.gov from April 2021 for use with the TREC Clinical Trials 2021 Track.

Dataset information

docs Metadata

376K docs

Language: en

Document type:

ClinicalTrialsDoc: (namedtuple)

doc_id: str
title: str
condition: str
summary: str
detailed_description: str
eligibility: str

Examples:

Python API CLI PyTerrier

import ir_datasets
dataset = ir_datasets.load("clinicaltrials/2021")
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, title, condition, summary, detailed_description, eligibility>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2021 docs



[doc_id]    [title]    [condition]    [summary]    [detailed_description]    [eligibility]
...

You can find more details about the CLI here.

{
  "docs": {
    "count": 375580,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  }
}

`"clinicaltrials/2021/trec-ct-2021"`

The TREC Clinical Trials 2021 track.

Shared Task Website

queries docs qrels Metadata

75 queries

Language: en

Query type:

GenericQuery: (namedtuple)

query_id: str
text: str

Examples:

Python API CLI PyTerrier

import ir_datasets
dataset = ir_datasets.load("clinicaltrials/2021/trec-ct-2021")
for query in dataset.queries_iter():
    query # namedtuple<query_id, text>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2021/trec-ct-2021 queries



[query_id]    [text]
...

You can find more details about the CLI here.

Rel.	Definition	Count	%
0	Not Relevant	`24K`	67.7%
1	Excluded	`6.0K`	16.8%
2	Eligible	`5.6K`	15.5%

{
  "docs": {
    "count": 375580,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  },
  "queries": {
    "count": 75
  },
  "qrels": {
    "count": 35832,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "1": 6019,
          "0": 24243,
          "2": 5570
        }
      }
    }
  }
}

`"clinicaltrials/2021/trec-ct-2022"`

The TREC Clinical Trials 2022 track.

Shared Task Website

queries docs Metadata

50 queries

Language: en

Query type:

GenericQuery: (namedtuple)

query_id: str
text: str

Examples:

Python API CLI PyTerrier

import ir_datasets
dataset = ir_datasets.load("clinicaltrials/2021/trec-ct-2022")
for query in dataset.queries_iter():
    query # namedtuple<query_id, text>

You can find more details about the Python API here.

ir_datasets export clinicaltrials/2021/trec-ct-2022 queries



[query_id]    [text]
...

You can find more details about the CLI here.

{
  "docs": {
    "count": 375580,
    "fields": {
      "doc_id": {
        "max_len": 11,
        "common_prefix": "NCT0"
      }
    }
  },
  "queries": {
    "count": 50
  }
}

ir_datasets: Clinical Trials

"clinicaltrials"

"clinicaltrials/2017"

"clinicaltrials/2017/trec-pm-2017"

"clinicaltrials/2017/trec-pm-2018"

"clinicaltrials/2019"

"clinicaltrials/2019/trec-pm-2019"

"clinicaltrials/2021"

"clinicaltrials/2021/trec-ct-2021"

"clinicaltrials/2021/trec-ct-2022"

`ir_datasets`: Clinical Trials

`"clinicaltrials"`

`"clinicaltrials/2017"`

`"clinicaltrials/2017/trec-pm-2017"`

`"clinicaltrials/2017/trec-pm-2018"`

`"clinicaltrials/2019"`

`"clinicaltrials/2019/trec-pm-2019"`

`"clinicaltrials/2021"`

`"clinicaltrials/2021/trec-ct-2021"`

`"clinicaltrials/2021/trec-ct-2022"`