tokens
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[ "Naloxone", "reverses", "the", "antihypertensive", "effect", "of", "clonidine", "." ]
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[ "2", "to", "2", "mg", "/", "kg", "." ]
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[ "The", "hypotensive", "effect", "of", "100", "mg", "/", "kg", "alpha-methyldopa", "was", "also", "partially", "reversed", "by", "naloxone", "." ]
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[ "Naloxone", "alone", "did", "not", "affect", "either", "blood", "pressure", "or", "heart", "rate", "." ]
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[ "Suxamethonium", "infusion", "rate", "and", "observed", "fasciculations", "." ]
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[ "25", "mg", "s", "-", "1", "to", "20", "mg", "s", "-", "1", "." ]
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[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 3, 0 ]
[ "After", "her", "strength", "returned", ",", "repetitive", "stimulation", "was", "normal", ",", "but", "single", "fiber", "EMG", "revealed", "increased", "jitter", "and", "blocking", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "Her", "acetylcholine", "receptor", "antibody", "level", "was", "markedly", "elevated", "." ]
[ 0, 1, 0, 0, 0, 0, 0, 0, 0 ]
[ "Although", "paralysis", "after", "magnesium", "administration", "has", "been", "described", "in", "patients", "with", "known", "myasthenia", "gravis", ",", "it", "has", "not", "previously", "been", "reported", "to", "be", "the", "initial", "or", "only", "manifestation", "of", "the", "disease", "." ]
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[ "Patients", "who", "are", "unusually", "sensitive", "to", "the", "neuromuscular", "effects", "of", "magnesium", "should", "be", "suspected", "of", "having", "an", "underlying", "disorder", "of", "neuromuscular", "transmission" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 3, 3, 3 ]
[ "Chloroacetaldehyde", "and", "its", "contribution", "to", "urotoxicity", "during", "treatment", "with", "cyclophosphamide", "or", "ifosfamide", "." ]
[ 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ]
[ "An", "experimental", "study", "/", "short", "communication", "." ]
[ 0, 0, 0, 0, 0, 0, 0 ]
[ "Based", "on", "clinical", "data", ",", "indicating", "that", "chloroacetaldehyde", "(", "CAA", ")", "is", "an", "important", "metabolite", "of", "oxazaphosphorine", "cytostatics", ",", "an", "experimental", "study", "was", "carried", "out", "in", "order", "to", "elucidate", "the", "role", "of", "CAA", "in", "the", "development", "of", "hemorrhagic", "cystitis", "." ]
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[ "The", "data", "demonstrate", "that", "CAA", "after", "i", "." ]
[ 0, 0, 0, 0, 1, 0, 0, 0 ]
[ "v", "." ]
[ 0, 0 ]
[ "administration", "does", "not", "contribute", "to", "bladder", "damage", "." ]
[ 0, 0, 0, 0, 0, 2, 3, 0 ]
[ "When", "instilled", "directly", "into", "the", "bladder", ",", "CAA", "exerts", "urotoxic", "effects", ",", "it", "is", ",", "however", ",", "susceptible", "to", "detoxification", "with", "mesna" ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 ]
[ "Source", "of", "pain", "and", "primitive", "dysfunction", "in", "migraine", ":", "an", "identical", "site", "?", "Twenty", "common", "migraine", "patients", "received", "a", "one", "sided", "frontotemporal", "application", "of", "nitroglycerin", "(", "10", "patients", ")", "or", "placebo", "ointment", "(", "10", "patients", ")", "in", "a", "double", "blind", "study", "." ]
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[ "Early", "onset", "migraine", "attacks", "were", "induced", "by", "nitroglycerin", "in", "seven", "out", "of", "10", "patients", "versus", "no", "patient", "in", "the", "placebo", "group", "." ]
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[ "Subsequently", "20", "migraine", "patients", ",", "who", "developed", "an", "early", "onset", "attack", "with", "frontotemporal", "nitroglycerin", ",", "received", "the", "drug", "in", "a", "second", "induction", "test", "at", "other", "body", "areas", "." ]
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[ "No", "early", "onset", "migraine", "was", "observed", "." ]
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[ "Thus", "the", "migraine", "-", "inducing", "effect", "of", "nitroglycerin", "seems", "to", "depend", "on", "direct", "stimulation", "of", "the", "habitual", "site", "of", "pain", ",", "suggesting", "that", "the", "frontotemporal", "region", "is", "of", "crucial", "importance", "in", "the", "development", "of", "a", "migraine", "crisis", "." ]
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[ "This", "is", "not", "consistent", "with", "a", "CNS", "origin", "of", "migraine" ]
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[ "Clotiazepam", "-", "induced", "acute", "hepatitis", "." ]
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[ "We", "report", "the", "case", "of", "a", "patient", "who", "developed", "acute", "hepatitis", "with", "extensive", "hepatocellular", "necrosis", ",", "7", "months", "after", "the", "onset", "of", "administration", "of", "clotiazepam", ",", "a", "thienodiazepine", "derivative", "." ]
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[ "Clotiazepam", "withdrawal", "was", "followed", "by", "prompt", "recovery", "." ]
[ 1, 0, 0, 0, 0, 0, 0, 0 ]
[ "The", "administration", "of", "several", "benzodiazepines", ",", "chemically", "related", "to", "clotiazepam", ",", "did", "not", "interfere", "with", "recovery", "and", "did", "not", "induce", "any", "relapse", "of", "hepatitis", "." ]
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[ "This", "observation", "shows", "that", "clotiazepam", "can", "induce", "acute", "hepatitis", "and", "suggests", "that", "there", "is", "no", "cross", "hepatotoxicity", "between", "clotiazepam", "and", "several", "benzodiazepines" ]
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Dataset Card for "tner/bc5cdr"

Dataset Summary

BioCreative V CDR NER dataset formatted in a part of TNER project. The original dataset consists of long documents which cannot be fed on LM because of the length, so we split them into sentences to reduce their size.

  • Entity Types: Chemical, Disease

Dataset Structure

Data Instances

An example of train looks as follows.

{
    'tags': [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0],
    'tokens': ['Fasciculations', 'in', 'six', 'areas', 'of', 'the', 'body', 'were', 'scored', 'from', '0', 'to', '3', 'and', 'summated', 'as', 'a', 'total', 'fasciculation', 'score', '.']
}

Label ID

The label2id dictionary can be found at here.

{
    "O": 0,
    "B-Chemical": 1,
    "B-Disease": 2,
    "I-Disease": 3,
    "I-Chemical": 4
}

Data Splits

name train validation test
bc5cdr 5228 5330 5865

Citation Information

@article{wei2016assessing,
  title={Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task},
  author={Wei, Chih-Hsuan and Peng, Yifan and Leaman, Robert and Davis, Allan Peter and Mattingly, Carolyn J and Li, Jiao and Wiegers, Thomas C and Lu, Zhiyong},
  journal={Database},
  volume={2016},
  year={2016},
  publisher={Oxford Academic}
}
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