| {"description": "MIMICause Dataset: A dataset for representation and automatic extraction of causal relation types from clinical notes.\nThe dataset has 2714 samples having both explicit and implicit causality in which entities are in the same sentence or different sentences.\nThe dataset has following nine semantic causal relations (with directionality) between entitities E1 and E2 in a text snippet:\n(1) Cause(E1,E2)\n(2) Cause(E2,E1)\n(3) Enable(E1,E2)\n(4) Enable(E2,E1)\n(5) Prevent(E1,E2)\n(6) Prevent(E2,E1)\n(7) Hinder(E1,E2)\n(8) Hinder(E2,E1)\n(9) Other\n", "citation": "@inproceedings{khetan-etal-2022-mimicause,\n title={MIMICause: Representation and automatic extraction of causal relation types from clinical notes},\n author={Vivek Khetan and Md Imbesat Hassan Rizvi and Jessica Huber and Paige Bartusiak and Bogdan Sacaleanu and Andrew Fano},\n booktitle ={Findings of the Association for Computational Linguistics: ACL 2022},\n month={may},\n year={2022},\n publisher={Association for Computational Linguistics},\n address={Dublin, The Republic of Ireland},\n url={},\n doi={},\n pages={},\n}\n", "homepage": "https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/", "license": "", "features": {"E1": {"dtype": "string", "id": null, "_type": "Value"}, "E2": {"dtype": "string", "id": null, "_type": "Value"}, "Text": {"dtype": "large_string", "id": null, "_type": "Value"}, "Label": {"num_classes": 9, "names": ["Cause(E1,E2)", "Cause(E2,E1)", "Enable(E1,E2)", "Enable(E2,E1)", "Prevent(E1,E2)", "Prevent(E2,E1)", "Hinder(E1,E2)", "Hinder(E2,E1)", "Other"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "mimicause", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 366250, "num_examples": 1953, "dataset_name": "mimicause"}, "validation": {"name": "validation", "num_bytes": 91323, "num_examples": 489, "dataset_name": "mimicause"}, "test": {"name": "test", "num_bytes": 52856, "num_examples": 272, "dataset_name": "mimicause"}}, "download_checksums": {"https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/mimicause.zip": {"num_bytes": 333362, "checksum": "00c4d30abc9bede6dfb79cebf41a838e92cffb1204c94de320f0be8fda4c358b"}}, "download_size": 333362, "post_processing_size": null, "dataset_size": 510429, "size_in_bytes": 843791} |