{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T20:08:02Z","timestamp":1779912482204,"version":"3.53.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T00:00:00Z","timestamp":1744588800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T00:00:00Z","timestamp":1744588800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116287"],"award-info":[{"award-number":["R01NS116287"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS126690"],"award-info":[{"award-number":["R01NS126690"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116287"],"award-info":[{"award-number":["R01NS116287"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS126690"],"award-info":[{"award-number":["R01NS126690"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116287"],"award-info":[{"award-number":["R01NS116287"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS126690"],"award-info":[{"award-number":["R01NS126690"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116287"],"award-info":[{"award-number":["R01NS116287"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS126690"],"award-info":[{"award-number":["R01NS126690"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116287"],"award-info":[{"award-number":["R01NS116287"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS126690"],"award-info":[{"award-number":["R01NS126690"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Seizure frequency is essential for evaluating epilepsy treatment, ensuring patient safety, and reducing risk for Sudden Unexpected Death in Epilepsy. As this information is often described in clinical narratives, this study presents an approach to extracting structured seizure frequency details from such unstructured text. We investigated two tasks: (1) extracting phrases describing seizure frequency, and (2) extracting seizure frequency attributes. For both tasks, we fine-tuned three BERT-based models (bert-large-cased, biobert-large-cased, and Bio_ClinicalBERT), as well as three generative large language models (GPT-4, GPT-3.5 Turbo, and Llama-2-70b-hf). The final structured output integrated the results from both tasks. GPT-4 attained the best performance across all tasks with precision, recall, and F1-score of 86.61%, 85.04%, and 85.79% respectively for frequency phrase extraction; 90.23%, 93.51%, and 91.84% for seizure frequency attribute extraction; and 86.64%, 85.06%, and 85.82% for the final structured output. These findings highlight the potential of fine-tuned generative models in extractive tasks from limited text strings.<\/jats:p>","DOI":"10.1038\/s41746-025-01592-4","type":"journal-article","created":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T11:08:57Z","timestamp":1744628937000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Leveraging pretrained language models for seizure frequency extraction from epilepsy evaluation reports"],"prefix":"10.1038","volume":"8","author":[{"given":"Rashmie","family":"Abeysinghe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiqiang","family":"Tao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samden D.","family":"Lhatoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guo-Qiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Licong","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,14]]},"reference":[{"key":"1592_CR1","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1053\/seiz.1999.0306","volume":"8","author":"JF Annegers","year":"1999","unstructured":"Annegers, J. F. & Coan, S. P. SUDEP: overview of definitions and review of incidence data. Seizure 8, 347\u2013352 (1999).","journal-title":"Seizure"},{"key":"1592_CR2","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1002\/epi4.12722","volume":"8","author":"G Giussani","year":"2023","unstructured":"Giussani, G. et al. Sudden unexpected death in epilepsy: a critical view of the literature. Epilepsia Open 8, 728\u2013757 (2023).","journal-title":"Epilepsia Open"},{"key":"1592_CR3","doi-asserted-by":"publisher","first-page":"1137182","DOI":"10.3389\/fneur.2023.1137182","volume":"14","author":"X Sun","year":"2023","unstructured":"Sun, X., Lv, Y. & Lin, J. The mechanism of sudden unexpected death in epilepsy: a mini review. Front. Neurol. 14, 1137182 (2023).","journal-title":"Front. Neurol."},{"key":"1592_CR4","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1038\/nrneurol.2014.64","volume":"10","author":"CA Massey","year":"2014","unstructured":"Massey, C. A., Sowers, L. P., Dlouhy, B. J. & Richerson, G. B. SUDEP mechanisms: the pathway to prevention. Nat. Rev. Neurol. 10, 271 (2014).","journal-title":"Nat. Rev. Neurol."},{"key":"1592_CR5","doi-asserted-by":"publisher","first-page":"1674","DOI":"10.1212\/WNL.0000000000003685","volume":"88","author":"C Harden","year":"2017","unstructured":"Harden, C. et al. Practice guideline summary: Sudden unexpected death in epilepsy incidence rates and risk factors: report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology and the American Epilepsy Society. Neurology 88, 1674\u20131680 (2017).","journal-title":"Neurology"},{"key":"1592_CR6","doi-asserted-by":"publisher","first-page":"1150","DOI":"10.1111\/j.1528-1167.2010.02952.x","volume":"52","author":"DC Hesdorffer","year":"2011","unstructured":"Hesdorffer, D. C. et al. Combined analysis of risk factors for SUDEP. Epilepsia 52, 1150\u20131159 (2011).","journal-title":"Epilepsia"},{"key":"1592_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.seizure.2006.10.002","volume":"16","author":"CPJA Mont\u00e9","year":"2007","unstructured":"Mont\u00e9, C. P. J. A. et al. Sudden unexpected death in epilepsy patients: risk factors: a systematic review. Seizure 16, 1\u20137 (2007).","journal-title":"Seizure"},{"key":"1592_CR8","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1111\/j.1528-1167.2005.00411.x","volume":"46","author":"T Tomson","year":"2005","unstructured":"Tomson, T., Walczak, T., Sillanpaa, M. & Sander, J. W. A. S. Sudden unexpected death in epilepsy: a review of incidence and risk factors. Epilepsia 46, 54\u201361 (2005).","journal-title":"Epilepsia"},{"key":"1592_CR9","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1080\/14737175.2018.1439738","volume":"18","author":"L Watkins","year":"2018","unstructured":"Watkins, L., Shankar, R. & Sander, J. W. Identifying and mitigating Sudden Unexpected Death in Epilepsy (SUDEP) risk factors. Expert Rev. Neurother. 18, 265\u2013274 (2018).","journal-title":"Expert Rev. Neurother."},{"key":"1592_CR10","doi-asserted-by":"publisher","first-page":"252","DOI":"10.3389\/fneur.2015.00252","volume":"6","author":"JL Novak","year":"2015","unstructured":"Novak, J. L., Miller, P. R., Markovic, D., Meymandi, S. K. & DeGiorgio, C. M. Risk assessment for sudden death in epilepsy: the SUDEP-7 inventory. Front. Neurol. 6, 252 (2015).","journal-title":"Front. Neurol."},{"key":"1592_CR11","first-page":"1248","volume":"2014","author":"G-Q Zhang","year":"2014","unstructured":"Zhang, G. -Q., Cui, L., Lhatoo, S., Schuele, S. U. & Sahoo, S. S. MEDCIS: multi-modality epilepsy data capture and integration system. Amia. Annu. Symp. Proc. 2014, 1248\u20131257 (2014).","journal-title":"Amia. Annu. Symp. Proc."},{"key":"1592_CR12","first-page":"466","volume":"2022","author":"S Tao","year":"2022","unstructured":"Tao, S., Cui, L., Chou, W. -C., Lhatoo, S. & Zhang, G. -Q. DaT3M: a data tracker for multi-faceted management of multi-site clinical research data submission, curation, master inventorying, and sharing. AMIA Summits Transl. Sci. Proc. 2022, 466\u2013475 (2022).","journal-title":"AMIA Summits Transl. Sci. Proc."},{"key":"1592_CR13","doi-asserted-by":"publisher","first-page":"965715","DOI":"10.3389\/fdata.2022.965715","volume":"5","author":"X Li","year":"2022","unstructured":"Li, X. et al. A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy. Front. Big Data 5, 965715 (2022).","journal-title":"Front. Big Data"},{"key":"1592_CR14","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1111\/epi.17474","volume":"64","author":"ANJ Yew","year":"2023","unstructured":"Yew, A. N. J., Schraagen, M., Otte, W. M. & van Diessen, E. Transforming epilepsy research: A systematic review on natural language processing applications. Epilepsia 64, 292\u2013305 (2023).","journal-title":"Epilepsia"},{"key":"1592_CR15","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.seizure.2022.07.010","volume":"101","author":"BM Decker","year":"2022","unstructured":"Decker, B. M. et al. Development of a natural language processing algorithm to extract seizure types and frequencies from the electronic health record. Seizure Eur. J. Epilepsy 101, 48\u201351 (2022).","journal-title":"Seizure Eur. J. Epilepsy"},{"key":"1592_CR16","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1093\/jamia\/ocac018","volume":"29","author":"K Xie","year":"2022","unstructured":"Xie, K. et al. Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing. J. Am. Med. Inform. Assoc. 29, 873\u2013881 (2022).","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"1592_CR17","doi-asserted-by":"publisher","unstructured":"Akiba, T., Sano, S., Yanase, T., Ohta, T. & Koyama, M. Optuna: a next-generation hyperparameter optimization framework. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2623\u20132631 (Association for Computing Machinery, New York, NY, USA, 2019). https:\/\/doi.org\/10.1145\/3292500.3330701.","DOI":"10.1145\/3292500.3330701"},{"key":"1592_CR18","doi-asserted-by":"publisher","first-page":"e22939","DOI":"10.2196\/22939","volume":"23","author":"S Tao","year":"2021","unstructured":"Tao, S., Lhatoo, S., Hampson, J., Cui, L. & Zhang, G. -Q. A bespoke electronic health record for epilepsy care (epitome): development and qualitative evaluation. J. Med. Internet Res. 23, e22939 (2021).","journal-title":"J. Med. Internet Res."},{"key":"1592_CR19","unstructured":"Deu\u00dfer, T., Hillebrand, L., Bauckhage, C. & Sifa, R. Informed named entity recognition decoding for generative language models. arXiv.org https:\/\/arxiv.org\/abs\/2308.07791v1 (2023)."},{"key":"1592_CR20","doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.-W., Lee, K. & Toutanova, K. BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) (eds. Burstein, J., Doran, C. & Solorio, T.) 4171\u20134186 (Association for Computational Linguistics, Minneapolis, Minnesota, 2019). https:\/\/doi.org\/10.18653\/v1\/N19-1423.","DOI":"10.18653\/v1\/N19-1423"},{"key":"1592_CR21","doi-asserted-by":"publisher","first-page":"1234","DOI":"10.1093\/bioinformatics\/btz682","volume":"36","author":"J Lee","year":"2020","unstructured":"Lee, J. et al. BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics 36, 1234\u20131240 (2020).","journal-title":"Bioinformatics"},{"key":"1592_CR22","doi-asserted-by":"publisher","unstructured":"Ramshaw, L. A. & Marcus, M. P. Text chunking using transformation-based learning. In: Natural Language Processing Using Very Large Corpora (eds. Armstrong, S. et al.) 157\u2013176 (Springer Netherlands, Dordrecht, 1999). https:\/\/doi.org\/10.1007\/978-94-017-2390-9_10.","DOI":"10.1007\/978-94-017-2390-9_10"},{"key":"1592_CR23","unstructured":"Zhang, S. et al. Instruction tuning for large language models: a survey. http:\/\/arxiv.org\/abs\/2308.10792 (2023)."},{"key":"1592_CR24","unstructured":"Xu, L., Xie, H., Qin, S.-Z. J., Tao, X. & Wang, F. L. Parameter-efficient fine-tuning methods for pretrained language models: a critical review and assessment. http:\/\/arxiv.org\/abs\/2312.12148 (2023)."},{"key":"1592_CR25","doi-asserted-by":"publisher","first-page":"e210258","DOI":"10.1148\/ryai.210258","volume":"4","author":"A Yan","year":"2022","unstructured":"Yan, A. et al. RadBERT: adapting transformer-based language models to radiology. Radiol. Artif. Intell. 4, e210258 (2022).","journal-title":"Radiol. Artif. Intell."},{"key":"1592_CR26","unstructured":"Koehn, P. Statistical significance tests for machine translation evaluation. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (eds. Lin, D. & Wu, D.) 388\u2013395 (Association for Computational Linguistics, Barcelona, Spain, 2004)."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01592-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01592-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01592-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T11:08:59Z","timestamp":1744628939000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01592-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,14]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1592"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-01592-4","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,14]]},"assertion":[{"value":"8 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"208"}}