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The utilization of large language models (LLMs) in the Healthcare domain has generated both excitement and concern due to their ability to effectively respond to freetext queries with certain professional knowledge. This survey outlines the…

计算与语言 · 计算机科学 2025-01-28 Kai He , Rui Mao , Qika Lin , Yucheng Ruan , Xiang Lan , Mengling Feng , Erik Cambria

Large Language Models (LLMs) have demonstrated remarkable versatility in recent years, offering potential applications across specialized domains such as healthcare and medicine. Despite the availability of various open-source LLMs tailored…

计算与语言 · 计算机科学 2024-07-18 Yanis Labrak , Adrien Bazoge , Emmanuel Morin , Pierre-Antoine Gourraud , Mickael Rouvier , Richard Dufour

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 recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs have only released partial artifacts, such as the final…

Large Language Models (LLMs) represent a revolution in AI. However, they also pose many significant risks, such as the presence of biased, private, copyrighted or harmful text. For this reason we need open, transparent and safe solutions.…

计算与语言 · 计算机科学 2023-10-24 Arno Candel , Jon McKinney , Philipp Singer , Pascal Pfeiffer , Maximilian Jeblick , Chun Ming Lee , Marcos V. Conde

Current-generation Large Language Models (LLMs) have stirred enormous interest in recent months, yielding great potential for accessibility and automation, while simultaneously posing significant challenges and risk of misuse. To facilitate…

As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields. In medicine, these LLMs hold considerable promise for…

Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are either closed-source…

With the rapid development of artificial intelligence, large language models (LLMs) have shown promising capabilities in mimicking human-level language comprehension and reasoning. This has sparked significant interest in applying LLMs to…

计算与语言 · 计算机科学 2023-11-06 Mingze Yuan , Peng Bao , Jiajia Yuan , Yunhao Shen , Zifan Chen , Yi Xie , Jie Zhao , Yang Chen , Li Zhang , Lin Shen , Bin Dong

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

Large Language Models (LLMs) are transforming mental health care by enhancing accessibility, personalization, and efficiency in therapeutic interventions. These AI-driven tools empower mental health professionals with real-time support,…

计算机与社会 · 计算机科学 2025-01-22 Hari Mohan Pandey

The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging demographic and a shortage of healthcare professionals.…

机器人学 · 计算机科学 2024-11-06 Souren Pashangpour , Goldie Nejat

Large language models (LLMs) have rapidly advanced natural language processing, driving significant breakthroughs in tasks such as text generation, machine translation, and domain-specific reasoning. The field now faces a critical dilemma…

计算与语言 · 计算机科学 2025-10-15 Jiya Manchanda , Laura Boettcher , Matheus Westphalen , Jasser Jasser

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

计算与语言 · 计算机科学 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

As the capabilities of Large Language Models (LLMs) in healthcare and medicine continue to advance, there is a growing need for competitive open-source models that can safeguard public interest. With the increasing availability of highly…

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

Digital health tools have the potential to significantly improve the delivery of healthcare services. However, their adoption remains comparatively limited due, in part, to challenges surrounding usability and trust. Large Language Models…

计算与语言 · 计算机科学 2024-03-01 Fergus Imrie , Paulius Rauba , Mihaela van der Schaar

This position paper analyzes the evolving roles of open-source and closed-source large language models (LLMs) in healthcare, emphasizing their distinct contributions and the scientific community's response to their development. Due to their…

计算机与社会 · 计算机科学 2025-01-20 Jiawei Xu , Ying Ding , Yi Bu

Large Language Models (LLMs) have made great strides in recent years to achieve unprecedented performance across different tasks. However, due to commercial interest, the most competitive models like GPT, Gemini, and Claude have been gated…

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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