{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:10:10Z","timestamp":1783577410937,"version":"3.55.0"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2023-00252257"],"award-info":[{"award-number":["RS-2023-00252257"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NRF Korean Government","award":["RS-2024-00397293"],"award-info":[{"award-number":["RS-2024-00397293"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/jbhi.2025.3561214","type":"journal-article","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T13:37:51Z","timestamp":1744724271000},"page":"7790-7801","source":"Crossref","is-referenced-by-count":5,"title":["MIFlu: Large Language Model-Based Multimodal Influenza Forecasting Scheme"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9835-360X","authenticated-orcid":false,"given":"Jaeuk","family":"Moon","sequence":"first","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9738-1038","authenticated-orcid":false,"given":"Jonghwa","family":"Shim","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5535-0655","authenticated-orcid":false,"given":"Eunbeen","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0418-4092","authenticated-orcid":false,"given":"Eenjun","family":"Hwang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Korea University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Seasonal influenza newsroom","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2021.017435"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411975"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210077"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2021.3093897"},{"issue":"8","key":"ref6","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i3.27963"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2023.3342137"},{"key":"ref9","first-page":"43322","article-title":"One fits all: Power general time series analysis by pre-trained LM","volume-title":"Proc. 37th Int. Conf. Neural Inform. Process. Syst.","author":"Zhou"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2023.3247687"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref12","article-title":"Reformer: The efficient transformer","author":"Kitaev","year":"2020"},{"key":"ref13","first-page":"22419","article-title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting","volume-title":"Proc. 35th Int. Conf. Neural Inform. Process. Syst.","author":"Wu"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2024.3377529"},{"key":"ref15","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. ACL Int. Conf. North Amer. Comp. Ling.","author":"Devlin","year":"2019"},{"key":"ref16","first-page":"1","article-title":"Improving language understanding by generative pre-training","volume":"1","author":"Radford","year":"2018","journal-title":"OpenAI Blog"},{"key":"ref17","article-title":"Llama 2: Open foundation and fine-tuned chat models","author":"Touvron","year":"2023"},{"key":"ref18","article-title":"Time-LLM: Time series forecasting by reprogramming large language models","volume-title":"Proc. 12th Int. Conf. Learn. Representations","author":"Jin","year":"2023"},{"key":"ref19","article-title":"Reversible instance normalization for accurate timeseries forecasting against distribution shift","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kim"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3037063"},{"key":"ref21","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Houlsby"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11651"},{"key":"ref23","article-title":"Partial fine-tuning: A successor to full fine-tuning for vision transformers","author":"Ye","year":"2023"},{"key":"ref24","article-title":"LoRA: Low-rank adaptation of large language models","author":"Hu","year":"2021"},{"key":"ref25","article-title":"National, regional, and state level outpatient illness and viral surceillance","year":"2024"},{"key":"ref26","article-title":"TimesNet: Temporal 2D-variation modeling for general time series analysis","author":"Wu","year":"2022"},{"key":"ref27","article-title":"ETSformer: Exponential smoothing transformers for time-series forecasting","author":"Woo","year":"2022"},{"key":"ref28","article-title":"Less is more: Fast multivariate time series forecasting with light sampling-oriented MLP structures","author":"Zhang","year":"2022"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref30","first-page":"27268","article-title":"FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting","volume-title":"Proc. 39th Int. Conf. Mach. Learn.","author":"Zhou","year":"2022"},{"key":"ref31","article-title":"A time series is worth 64 words: Long-term forecasting with transformers","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Nie","year":"2023"},{"key":"ref32","first-page":"9881","article-title":"Non-stationary transformers: Exploring the stationarity in time series forecasting","volume-title":"Proc. 36th Int. Conf. Neural Inform. Process. Syst.","author":"Liu"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2021.03.012"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104482"},{"key":"ref36","article-title":"LLM4TS: Two-stage fine-tuning for time-series forecasting with pre-trained LLMs","author":"Chang","year":"2023"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02249"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221020\/11192794\/10965883.pdf?arnumber=10965883","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T18:34:35Z","timestamp":1765305275000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10965883\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":37,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2025.3561214","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}