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相关论文: Towards a Personal Health Large Language Model

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We present DM-Bench, the first benchmark designed to evaluate large language model (LLM) performance across real-world decision-making tasks faced by individuals managing diabetes in their daily lives. Unlike prior health benchmarks that…

机器学习 · 计算机科学 2025-10-06 Maria Ana Cardei , Josephine Lamp , Mark Derdzinski , Karan Bhatia

Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective on using LLMs in mental health applications. It discusses…

计算与语言 · 计算机科学 2023-12-19 Shaoxiong Ji , Tianlin Zhang , Kailai Yang , Sophia Ananiadou , Erik Cambria

The deployment of large language models (LLMs) in healthcare has demonstrated substantial potential for enhancing clinical decision-making, administrative efficiency, and patient outcomes. However, the underrepresentation of diverse groups…

Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a burgeoning trend in research focusing on the employment of…

Large Language Models (LLMs) have fundamentally transformed approaches to Natural Language Processing (NLP) tasks across diverse domains. In healthcare, accurate and cost-efficient text classification is crucial, whether for clinical notes…

计算与语言 · 计算机科学 2026-02-16 Hajar Sakai , Sarah S. Lam

Discharge Summaries are documents written by medical professionals that detail a patient's visit to a care facility. They contain a wealth of information crucial for patient care, and automating their generation could significantly reduce…

计算与语言 · 计算机科学 2025-12-09 Tiago Rodrigues , Carla Teixeira Lopes

Large language models (LLMs) often lack specialized knowledge for complex bioinformatics applications. We present a reproducible pipeline for fine-tuning LLMs on specialized bioinformatics data, demonstrated through two use cases: PRSGPT,…

计算与语言 · 计算机科学 2026-01-21 Muhammad Muneeb , David B. Ascher

Large Language Models (LLMs) consistently excel in diverse medical Natural Language Processing (NLP) tasks, yet their substantial computational requirements often limit deployment in real-world healthcare settings. In this work, we…

计算与语言 · 计算机科学 2026-02-20 Pietro Ferrazzi , Mattia Franzin , Alberto Lavelli , Bernardo Magnini

This study evaluates the capacity of large language models (LLMs) to generate structured clinical consultation templates for electronic consultation. Using 145 expert-crafted templates developed and routinely used by Stanford's eConsult…

The healthcare industry is currently experiencing an unprecedented wave of cybersecurity attacks, impacting millions of individuals. With the discovery of thousands of vulnerabilities each month, there is a pressing need to drive the…

计算与语言 · 计算机科学 2024-07-23 Rikhiya Ghosh , Oladimeji Farri , Hans-Martin von Stockhausen , Martin Schmitt , George Marica Vasile

Digital health interventions increasingly deliver home exercise programs via sensor-equipped devices such as smartphones, enabling remote monitoring of adherence and performance. However, current software is usually authored before clinical…

Large language models (LLMs) have transformed natural language processing, yet face challenges in specialized tasks such as simulating opinions on environmental policies. This paper introduces a novel fine-tuning approach that integrates…

计算与语言 · 计算机科学 2024-12-10 Haocheng Lin

While Large Language Models (LLMs) have exhibited remarkable emergent capabilities through extensive pre-training, they still face critical limitations in generalizing to specialized domains and handling diverse linguistic variations, known…

计算与语言 · 计算机科学 2025-05-28 Jinwu Hu , Zhitian Zhang , Guohao Chen , Xutao Wen , Chao Shuai , Wei Luo , Bin Xiao , Yuanqing Li , Mingkui Tan

In an era dominated by Large Language Models (LLMs), understanding their capabilities and limitations, especially in high-stakes fields like law, is crucial. While LLMs such as Meta's LLaMA, OpenAI's ChatGPT, Google's Gemini, DeepSeek, and…

计算与语言 · 计算机科学 2025-09-29 Antreas Ioannou , Andreas Shiamishis , Nora Hollenstein , Nezihe Merve Gürel

Understanding the conversation abilities of Large Language Models (LLMs) can help lead to its more cautious and appropriate deployment. This is especially important for safety-critical domains like mental health, where someone's life may…

计算与语言 · 计算机科学 2024-03-18 Alexander Marrapese , Basem Suleiman , Imdad Ullah , Juno Kim

We explore the usage of large language models (LLM) in human-in-the-loop human-in-the-plant cyber-physical systems (CPS) to translate a high-level prompt into a personalized plan of actions, and subsequently convert that plan into a…

人工智能 · 计算机科学 2024-05-21 Ayan Banerjee , Aranyak Maity , Payal Kamboj , Sandeep K. S. Gupta

The demand for psychological counselling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which has heightened the need for timely and professional mental health support. Online psychological…

计算与语言 · 计算机科学 2023-09-04 Tin Lai , Yukun Shi , Zicong Du , Jiajie Wu , Ken Fu , Yichao Dou , Ziqi Wang

Empowered by vast internal knowledge reservoir, the new generation of large language models (LLMs) demonstrate untapped potential to tackle medical tasks. However, there is insufficient effort made towards summoning up a synergic effect…

计算与语言 · 计算机科学 2025-05-23 Kexin Shang , Chia-Hsuan Chang , Christopher C. Yang

Advances in large language models (LLMs) provide new opportunities in healthcare for improved patient care, clinical decision-making, and enhancement of physician and administrator workflows. However, the potential of these models…

Motivated by the remarkable progress of large language models (LLMs) in objective tasks like mathematics and coding, there is growing interest in their potential to simulate human behavior--a capability with profound implications for…

计算与语言 · 计算机科学 2026-01-23 Yuxuan Lei , Tianfu Wang , Jianxun Lian , Zhengyu Hu , Defu Lian , Xing Xie
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