Agrawal, M., Hegselmann, S., Lang, H., Kim, Y., & Sontag, D. (2022). Large language models are few-shot clinical information extractors. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.emnlp-main.130

Agrawal, Monica, Stefan Hegselmann, Hunter Lang, Yoon Kim, and David Sontag. “Large language models are few-shot clinical information extractors.” In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2022. https://doi.org/10.18653/v1/2022.emnlp-main.130.

Agrawal M, Hegselmann S, Lang H, Kim Y, Sontag D. Large language models are few-shot clinical information extractors. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics; 2022.

Agrawal, Monica, et al. “Large language models are few-shot clinical information extractors.” Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2022. Crossref, doi:10.18653/v1/2022.emnlp-main.130.

Agrawal M, Hegselmann S, Lang H, Kim Y, Sontag D. Large language models are few-shot clinical information extractors. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics; 2022.