{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T16:07:36Z","timestamp":1777392456359,"version":"3.51.4"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Institut de Valorisation des donn\u00e9es de l\u2019Universit\u00e9 de Montr\u00e9al"},{"DOI":"10.13039\/501100020951","name":"Fonds de la recherche en sante du Quebec","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020951","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3582037","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T17:35:03Z","timestamp":1750786503000},"page":"109365-109377","source":"Crossref","is-referenced-by-count":4,"title":["The Impact of LoRA Adapters on LLMs for Clinical Text Classification Under Computational and Data Constraints"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0782-8698","authenticated-orcid":false,"given":"Thanh-Dung","family":"Le","sequence":"first","affiliation":[{"name":"Biomedical Information Processing Laboratory, &#x00C9;cole de Technologie Sup&#x00E9;rieure, Montreal, QC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3933-2486","authenticated-orcid":false,"given":"Ti","family":"Ti Nguyen","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Esch-sur-Alzette, Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1325-3480","authenticated-orcid":false,"given":"Vu","family":"Nguyen Ha","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Esch-sur-Alzette, Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5122-0001","authenticated-orcid":false,"given":"Symeon","family":"Chatzinotas","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, Esch-sur-Alzette, Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5684-3398","authenticated-orcid":false,"given":"Philippe","family":"Jouvet","sequence":"additional","affiliation":[{"name":"CHU Sainte-Justine Research Center, CHU Sainte-Justine Hospital, University of Montreal, Montreal, QC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4519-1686","authenticated-orcid":false,"given":"Rita","family":"Noumeir","sequence":"additional","affiliation":[{"name":"Biomedical Information Processing Laboratory, &#x00C9;cole de Technologie Sup&#x00E9;rieure, Montreal, QC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Exploring the limits of language modeling","author":"Jozefowicz","year":"2016","journal-title":"arXiv:1602.02410"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"issue":"8","key":"ref3","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"ref4","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Brown"},{"key":"ref5","article-title":"Scaling laws for neural language models","author":"Kaplan","year":"2020","journal-title":"arXiv:2001.08361"},{"key":"ref6","article-title":"GPT-4 technical report","volume-title":"arXiv:2303.08774","author":"Achiam","year":"2023"},{"key":"ref7","first-page":"1","article-title":"The illustrated transformer","volume":"27","author":"Alammar","year":"2018","journal-title":"The Illustrated Transformer\u2013Jay Alammar\u2013Visualizing Machine Learning One Concept At a Time"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0291"},{"issue":"5","key":"ref9","first-page":"299","article-title":"Pediatric acute respiratory distress syndrome: Consensus recommendations from the pediatric acute lung injury consensus conference","volume":"22","year":"2015","journal-title":"Pediatric Crit. Care Med., J. Soc. Crit. Care Med. World Fed. Pediatric Intensive Crit. Care Societies"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1097\/CCE.0000000000000546"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2014.06.006"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC44109.2020.9176033"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/OJEMB.2022.3209900"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JTEHM.2023.3241635"},{"key":"ref15","article-title":"Are medium-sized transformers models still relevant for medical records processing?","author":"Aser Lompo","year":"2024","journal-title":"arXiv:2404.10171"},{"key":"ref16","article-title":"Multi-objective representation for numbers in clinical narratives: A CamemBERT-Bio-based alternative to large-scale LLMs","author":"Aser Lompo","year":"2024","journal-title":"arXiv:2405.18448"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/jtehm.2025.3576570"},{"key":"ref18","article-title":"GRN-transformer: Enhancing motion artifact detection in PICU photoplethysmogram signals","author":"Le","year":"2023","journal-title":"arXiv:2308.03722"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3349952"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3365742"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06291-2"},{"key":"ref22","article-title":"When scaling meets LLM finetuning: The effect of data, model and finetuning method","volume-title":"Proc. 12th Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.168"},{"key":"ref24","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Hu"},{"key":"ref25","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Houlsby"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.7"},{"key":"ref27","first-page":"16664","article-title":"AdaptFormer: Adapting vision transformers for scalable visual recognition","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chen"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-short.103"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.444"},{"key":"ref30","article-title":"Transformer meets gated residual networks to enhance photoplethysmogram artifact detection informed by mutual information neural estimation","author":"Le","year":"2024","journal-title":"arXiv:2405.16177"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-4015"},{"key":"ref32","article-title":"CamemBERT-bio: Leveraging continual pre-training for cost-effective models on French biomedical data","author":"Touchent","year":"2023","journal-title":"arXiv:2306.15550"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.896"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.bionlp-1.19"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3411774"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-023-00626-4"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"ref38","volume-title":"Keras","author":"Chollet","year":"2015"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.2478\/pralin-2018-0002"},{"issue":"1","key":"ref40","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref41","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref43","first-page":"7694","article-title":"Understanding batch normalization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bjorck"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"ref45","article-title":"LoRA learns less and forgets less","author":"Biderman","year":"2024","journal-title":"arXiv:2405.09673"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp2405999"},{"key":"ref47","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.5169443","volume-title":"Evaluation of LLMs accuracy and application in oncology principles and practice","author":"Liang","year":"2025"},{"key":"ref48","article-title":"Mamba: Linear-time sequence modeling with selective state spaces","author":"Gu","year":"2023","journal-title":"arXiv:2312.00752"},{"key":"ref49","article-title":"Tina: Tiny reasoning models via LoRA","author":"Wang","year":"2025","journal-title":"arXiv:2504.15777"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11048527.pdf?arnumber=11048527","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T05:28:10Z","timestamp":1751347690000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11048527\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3582037","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}