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--- |
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license: mit |
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task_categories: |
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- text-classification |
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tags: |
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- medical |
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size_categories: |
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- 10K<n<100K |
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--- |
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**CTMatch Dataset** |
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This is a combined set of 2 labelled datasets of: |
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`topic (patient descriptions), doc (clinical trials documents - selected fields), and label ({0, 1, 2})` triples, in jsonl format. |
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(Somewhat of a duplication of some of the `ir_dataset` also available on HF.) |
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These have been processed using ctproc, and in this state can be used by various tokenizers for fine-tuning (see ctmatch for examples). |
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These 2 datasets contain no patient identifying information are openly available in raw forms: |
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#### TREC: http://www.trec-cds.org/2021.html |
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#### CSIRO: https://data.csiro.au/collection/csiro:17152 |
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--- |
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Additionally, for the IR task, other feature representations of the unlabelled documents have been created. |
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Each of these has exactly 374648 lines of corresponding data: |
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`doc_texts.csv` |
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- texts extracted from processed documents using several fields including eligbility min and max age, and eligbility criteria, structured as this example from NCT00000102: |
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"Inclusion Criteria: diagnosed with Congenital Adrenal Hyperplasia (CAH) normal ECG during baseline evaluation, Exclusion Criteria: history of liver disease, or elevated liver function tests history of cardiovascular disease" |
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`doc_categories.csv`: |
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- 1 x 15 vectors of somewhat arbitrarily chosen topic probabilities (softmax output) generated by zero-shot classification model, CTMatch.category_model(doc['condition']) lexically ordered as such: |
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cancer,cardiac,endocrine,gastrointestinal,genetic,healthy,infection,neurological,other,pediatric,psychological,pulmonary,renal,reproductive |
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`doc_embeddings.csv`: |
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- 1 x 384 vectors of embeddings taken from last hidden state of CTMatch.embedding_model.encode(doc_text) using SentenceTransformers |
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`index2docid.csv`: |
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- simple mapping of index to NCTID's for filtering/reference throughout IR program, corresponding to vector, texts representation order |
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**see repo for more information**: |
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https://github.com/semajyllek/ctmatch |
