Datasets › DisKnE
DisKnE (Disease Knowledge Evaluation)
DisKnE is a benchmark for Disease Knowledge Evaluation built from MedNLI and MEDIQA-NLI. This benchmark is constructed to specifically test the medical reasoning capabilities of ML models, such as mapping symptoms to diseases.
The dataset was built by annotating each positive MedNLI example with the types of medical reasoning that are needed. Negative examples were created by corrupting these positive examples in an adversarial way. Furthermore, the training-test splits are defined per disease, ensuring that no knowledge about test diseases can be learned from the training data.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
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License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- DisKnE
1 variant name, as the archive lists them.
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