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pro vyhledávání: '"Moore, Callandra"'
Automated deidentification of clinical text data is crucial due to the high cost of manual deidentification, which has been a barrier to sharing clinical text and the advancement of clinical natural language processing. However, creating effective au
Externí odkaz:
http://arxiv.org/abs/2311.02748
We investigated whether large language models (LLMs) can develop data validation tests. We considered 96 conditions each for both GPT-3.5 and GPT-4, examining different prompt scenarios, learning modes, temperature settings, and roles. The prompt sce
Externí odkaz:
http://arxiv.org/abs/2310.01402
Autor:
Katz, Lindsay, Moore, Callandra
This paper describes a series of automated data validation tests for datasets detailing charity financial information, political donations, and government lobbying in Canada. We motivate and document a series of 200 tests that check the validity, int
Externí odkaz:
http://arxiv.org/abs/2309.12886