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Large language models (LLMs) have demonstrated powerful text generation capabilities, bringing unprecedented innovation to the healthcare field.
Bodenreider, O.: The unified medical language system (umls): integrating biomedical terminology. Nucleic acids research 32
2004
Earlier work this paper cites.
Lin, C.-Y.: Rouge: A package for automatic evaluation of summaries. In: Text Summarization Branches Out, pp. 74–81 (2004)
2004
Earlier work this paper cites.
Abacha, A.B., Agichtein, E., Pinter, Y., Demner-Fushman, D.: Overview of the medical question answering task at trec 2017 liveqa. In: TREC, pp. 1–12 (2017)
2017
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2020
Earlier work this paper cites.
Lu, Q., Dou, D., Nguyen, T.H.: Parameter-efficient domain knowledge integration from multiple sources for biomedical pre-trained language models. In: Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 3855–3865 (2021)
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
2022
Cited alongside, same era.
Li, I., Pan, J., Goldwasser, J., Verma, N., Wong, W.P., Nuzumlalı, M.Y., Rosand, B., Li, Y., Zhang, M., Chang, D., et al
2022
Cited alongside, same era.
Aracena, C., Villena, F., Rojas, M., Dunstan, J.: A knowledge-graph-based intrinsic test for benchmarking medical concept embeddings and pretrained language models. In: Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI), pp. 197–206 (2022)
2022
Cited alongside, same era.
Raza, S., Reji, D.J., Shajan, F., Bashir, S.R.: Large-scale application of named entity recognition to biomedicine and epidemiology. PLOS Digital Health 1
2022
Cited alongside, same era.
Xie, Q., Schenck, E.J., Yang, H.S., Chen, Y., Peng, Y., Wang, F.: Faithful ai in medicine: A systematic review with large language models and beyond. Medrxiv: the Preprint Server for Health Sciences (2023)
2023
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Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., Neal, D., Schaekermann, M., Wang, A., Amin, M., Lachgar, S., Mansfield, P., Prakash, S., Green, B., Dominowska, E., Arcas, B.A., Tomasev, N., Liu, Y., Wong, R., Semturs, C., Mahdavi, S.S., Barral, J., Webster, D., Corrado, G.S., Matias, Y., Azizi, S., Karthikesalingam, A., Natarajan, V.: Towards Expert-Level Medical Question Answering with Large Language Models (2023)
2023
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2023
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OpenAI: GPT-4 Technical Report (2023)
2023
Cited alongside, same era.
2023
Cited alongside, same era.
Yang, R., Tan, T.F., Lu, W., Thirunavukarasu, A.J., Ting, D.S.W., Liu, N.: Large language models in health care: Development, applications, and challenges. Health Care Science (2023)
2023
Cited alongside, same era.
2023
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Long, C., Subburam, D., Lowe, K., Santos, A.d., Zhang, J., Hwang, S., Saduka, N., Horev, Y., Su, T., Cote, D., et al.: Chatent: Augmented large language model for expert knowledge retrieval in otolaryngology-head and neck surgery. medRxiv, 2023–08 (2023)
2023
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Malaviya, C., Lee, S., Chen, S., Sieber, E., Yatskar, M., Roth, D.: ExpertQA: Expert-Curated Questions and Attributed Answers (2023)
2023
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