Yuhao Zhang, Matthew Lungren, Andrew Ng, Pranav Rajpurkar, Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Qh, Truong Vinbrain, Vinuniversity Du, Nguyen Duong, Tan Bui, and 2 more
We lifted 9 functions out of this paper's own repositories and ran 5 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| rajpurkarlab/cxr-report-metric | pwc_unofficial | 5 of 9 |
| Function | Status | Where it lives |
|---|---|---|
| compute_f1 | Ran | rajpurkarlab/cxr-report-metric/CXRMetric/radgraph_evaluate_model.py code served (permissive licence) · get_code("b59ac1362f3babba") |
| get_impressions_from_csv | Ran | rajpurkarlab/cxr-report-metric/CXRMetric/CheXbert/src/bert_tokenizer.py code served (permissive licence) · get_code("eea5e5d8721b8cbb") |
| load_list | Ran | rajpurkarlab/cxr-report-metric/CXRMetric/CheXbert/src/bert_tokenizer.py code served (permissive licence) · get_code("8af312e6bf3486f6") |
| parse_entity_relation | Ran | rajpurkarlab/cxr-report-metric/CXRMetric/radgraph_evaluate_model.py code served (permissive licence) · get_code("71d87fbd996af446") |
| prep_reports | Ran | rajpurkarlab/cxr-report-metric/CXRMetric/run_eval.py code served (permissive licence) · get_code("9c02cf5d9fb1729c") |
| batch_identity | Not yet run | rajpurkarlab/cxr-report-metric/dygie/models/shared.py code served (permissive licence) · get_code("bbc5dc5142133340") |
| cumsum_shifted | Not yet run | rajpurkarlab/cxr-report-metric/dygie/models/shared.py code served (permissive licence) · get_code("7e0b52001d4f5323") |
| fields_to_batches | Not yet run | rajpurkarlab/cxr-report-metric/dygie/models/shared.py code served (permissive licence) · get_code("1b01fb249fb7cd71") |
| tokenize | Not yet run | rajpurkarlab/cxr-report-metric/CXRMetric/CheXbert/src/bert_tokenizer.py code served (permissive licence) · get_code("c98cb8be7d52c5c5") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Extracting structured clinical information from free-text radiology reports can enable the use of radiology report information for a variety of critical healthcare applications. In our work, we present RadGraph, a dataset of entities and relations in full-text chest X-ray radiology reports based on a novel information extraction schema we designed to structure radiology reports. We release a development dataset, which contains board-certified radiologist annotations for 500 radiology reports from the MIMIC-CXR dataset (14,579 entities and 10,889 relations), and a test dataset, which contains two independent sets of board-certified radiologist annotations for 100 radiology reports split equally across the MIMIC-CXR and CheXpert datasets. Using these datasets, we train and test a deep learning model, RadGraph Benchmark, that achieves a micro F1 of 0.82 and 0.73 on relation extraction on the MIMIC-CXR and CheXpert test sets respectively. Additionally, we release an inference dataset, which contains annotations automatically generated by RadGraph Benchmark across 220,763 MIMIC-CXR reports (around 6 million entities and 4 million relations) and 500 CheXpert reports (13,783 entities and 9,908 relations) with mappings to associated chest radiographs. Our freely available dataset can facilitate a wide range of research in medical natural language processing, as well as computer vision and multi-modal learning when linked to chest radiographs.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2106.14463")
get_code_for_paper("2106.14463")
have("2106.14463")
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