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Large language models (LLMs) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their proficiency in various tasks, LLMs like PaLM 540B and Llama-3.1…

Large language models (LLMs) show promise for supporting clinical decision-making in complex fields such as rheumatology. Our evaluation shows that smaller language models (SLMs), combined with retrieval-augmented generation (RAG), achieve…

Small Language Models (SLMs) have gained substantial attention due to their ability to execute diverse language tasks successfully while using fewer computer resources. These models are particularly ideal for deployment in limited…

计算与语言 · 计算机科学 2025-05-30 Tanjil Hasan Sakib , Md. Tanzib Hosain , Md. Kishor Morol

Large Language Models (LLMs) have demonstrated surprising performance across various natural language processing tasks. Recently, medical LLMs enhanced with domain-specific knowledge have exhibited excellent capabilities in medical…

计算与语言 · 计算机科学 2024-09-24 Jinqiang Wang , Huansheng Ning , Yi Peng , Qikai Wei , Daniel Tesfai , Wenwei Mao , Tao Zhu , Runhe Huang

Despite substantial progress in healthcare applications driven by large language models (LLMs), growing concerns around data privacy, and limited resources; the small language models (SLMs) offer a scalable and clinically viable solution…

计算与语言 · 计算机科学 2025-04-28 Muskan Garg , Shaina Raza , Shebuti Rayana , Xingyi Liu , Sunghwan Sohn

Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, making them ideal for various settings including on-device,…

Background: Large Language Models (LLMs) are transforming artificial intelligence applications in healthcare due to their ability to understand, generate, and summarize complex medical text. They offer valuable support to clinicians,…

计算与语言 · 计算机科学 2026-04-14 Subin Santhosh , Farwa Abbas , Hussain Ahmad , Claudia Szabo

The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering (QA) task with answer options for evaluation. However, many clinical…

Recently, Large Language Models (LLM) have demonstrated impressive capability to solve a wide range of tasks. However, despite their success across various tasks, no prior work has investigated their capability in the biomedical domain yet.…

计算与语言 · 计算机科学 2024-02-21 Israt Jahan , Md Tahmid Rahman Laskar , Chun Peng , Jimmy Huang

Existing benchmarks for evaluating the clinical reasoning capabilities of large language models (LLMs) often lack a clear definition of "clinical reasoning" as a construct, fail to capture the full breadth of interdependent tasks within a…

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable capability to provide proficient responses to free-text queries, demonstrating a…

计算与语言 · 计算机科学 2024-07-09 Zabir Al Nazi , Wei Peng

Large language models (LLMs) hold promise for transforming healthcare, from streamlining administrative and clinical workflows to enriching patient engagement and advancing clinical decision-making. However, their successful integration…

计算机与社会 · 计算机科学 2025-04-04 Mohammed Al-Garadi , Tushar Mungle , Abdulaziz Ahmed , Abeed Sarker , Zhuqi Miao , Michael E. Matheny

The application of large language models (LLMs) in healthcare has gained significant attention due to their ability to process complex medical data and provide insights for clinical decision-making. These models have demonstrated…

计算机视觉与模式识别 · 计算机科学 2024-09-26 Amna Khalid , Ayma Khalid , Umar Khalid

Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPMs) for diagnostic and prognostic tasks, with a focus on…

计算机与社会 · 计算机科学 2025-11-07 Yusuf Yildiz , Goran Nenadic , Meghna Jani , David A. Jenkins

Large language models (LLMs) have emerged as powerful tools with transformative potential across numerous domains, including healthcare and medicine. In the medical domain, LLMs hold promise for tasks ranging from clinical decision support…

计算与语言 · 计算机科学 2024-05-14 Xiaolan Chen , Jiayang Xiang , Shanfu Lu , Yexin Liu , Mingguang He , Danli Shi

Large language models (LLMs) demonstrate remarkable medical expertise, but data privacy concerns impede their direct use in healthcare environments. Although offering improved data privacy protection, domain-specific small language models…

计算与语言 · 计算机科学 2024-05-17 Xinlu Zhang , Shiyang Li , Xianjun Yang , Chenxin Tian , Yao Qin , Linda Ruth Petzold

The advent of Large Language Models (LLMs) has ushered in a new era for design science in Information Systems, demanding a paradigm shift in tailoring LLMs design for business contexts. We propose and test a novel framework to customize…

计算机与社会 · 计算机科学 2024-05-15 Wen Wang , Zhenyue Zhao , Tianshu Sun

Small language models (SLMs), despite their widespread adoption in modern smart devices, have received significantly less academic attention compared to their large language model (LLM) counterparts, which are predominantly deployed in data…

计算与语言 · 计算机科学 2025-02-27 Zhenyan Lu , Xiang Li , Dongqi Cai , Rongjie Yi , Fangming Liu , Xiwen Zhang , Nicholas D. Lane , Mengwei Xu

Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ultimately improving individuals' quality of life. Previous studies on large language models (LLMs)…

人工智能 · 计算机科学 2025-10-01 Xin Wang , Ting Dang , Xinyu Zhang , Vassilis Kostakos , Michael J. Witbrock , Hong Jia

To address challenges in the digital economy's landscape of digital intelligence, large language models (LLMs) have been developed. Improvements in computational power and available resources have significantly advanced LLMs, allowing their…

计算与语言 · 计算机科学 2024-05-24 Yanxin Zheng , Wensheng Gan , Zefeng Chen , Zhenlian Qi , Qian Liang , Philip S. Yu
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