To Err Is Human, How about Medical Large Language Models? Comparing Pre-trained Language Models for Medical Assessment Errors and Reliability (2024.lrec-main)
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| Challenge: | a 1999 report found that at least forty thousand deaths are a result of preventable medical errors. |
| Approach: | They test pre-trained language models to characterize their error generation and reliability in medical assessment ability. |
| Outcome: | The results show that pre-trained models can generate errors and perform better than human models. |
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