Mitigating Sociodemographic Bias in Opioid Use Disorder Prediction: Fairness-Aware Machine Learning Framework [0.03%]
缓解阿片类药物使用障碍预测中的社会人口偏见：一种公平性感知的机器学习框架
Mohammad Yaseliani,Md Noor-E-Alam,Md Mahmudul Hasan
Mohammad Yaseliani
Background: Opioid use disorder (OUD) is a critical public health crisis in the United States, affecting >5.5 million Americans in 2021. Machine learning has been used to predict patient risk of incident OUD. However, lit...
Evaluating Literature Reviews Conducted by Humans Versus ChatGPT: Comparative Study [0.03%]
人机对比：文献综述评价之比较研究
Mehrnaz Mostafapour,Jacqueline H Fortier,Karen Pacheco et al.
Mehrnaz Mostafapour et al.
Background: With the rapid evolution of artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT-4 (OpenAI), there is an increasing interest in their potential to assist in scholarly tasks, ...
Giorgia Lorenzini,Laura Arbelaez Ossa,Stephen Milford et al.
Giorgia Lorenzini et al.
Background: The discourse surrounding medical artificial intelligence (AI) often focuses on narratives that either hype the technology's potential or predict dystopian futures. AI narratives have a significant influence o...
Evaluation of Generative Language Models in Personalizing Medical Information: Instrument Validation Study [0.03%]
生成语言模型在个性化医学信息中的评价：仪器验证研究
Aidin Spina,Saman Andalib,Daniel Flores et al.
Aidin Spina et al.
Background: Although uncertainties exist regarding implementation, artificial intelligence-driven generative language models (GLMs) have enormous potential in medicine. Deployment of GLMs could improve patient comprehensi...
Enhancing Clinical Relevance of Pretrained Language Models Through Integration of External Knowledge: Case Study on Cardiovascular Diagnosis From Electronic Health Records [0.03%]
通过集成外部知识增强预训练语言模型的临床相关性：电子健康记录中心血管诊断案例研究
Qiuhao Lu,Andrew Wen,Thien Nguyen et al.
Qiuhao Lu et al.
Background: Despite their growing use in health care, pretrained language models (PLMs) often lack clinical relevance due to insufficient domain expertise and poor interpretability. A key strategy to overcome these challe...
Automated Identification of Aspirin-Exacerbated Respiratory Disease Using Natural Language Processing and Machine Learning: Algorithm Development and Evaluation Study [0.03%]
基于自然语言处理和机器学习的自动化识别水杨酸盐加重性呼吸系统疾病：算法研发与评估研究
Thanai Pongdee,Nicholas B Larson,Rohit Divekar et al.
Thanai Pongdee et al.
Background: Aspirin-exacerbated respiratory disease (AERD) is an acquired inflammatory condition characterized by the presence of asthma, chronic rhinosinusitis with nasal polyposis, and respiratory hypersensitivity react...
Comparing the Efficacy and Efficiency of Human and Generative AI: Qualitative Thematic Analyses [0.03%]
人类与生成式AI的效能比较：定性主题分析
Maximo R Prescott,Samantha Yeager,Lillian Ham et al.
Maximo R Prescott et al.
Background: Qualitative methods are incredibly beneficial to the dissemination and implementation of new digital health interventions; however, these methods can be time intensive and slow down dissemination when timely k...
Predicting Workers' Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics [0.03%]
基于工作风格特性的高精度算法对劳动者过度紧张的预测研究
Hiroki Iwamoto,Saki Nakano,Ryotaro Tajima et al.
Hiroki Iwamoto et al.
Background: Work characteristics, such as teleworking rate, have been studied in relation to stress. However, the use of work-related data to improve a high-performance stress prediction model that suits an individual's l...
Can Large Language Models Replace Therapists? Evaluating Performance at Simple Cognitive Behavioral Therapy Tasks [0.03%]
大型语言模型能取代治疗师吗？简易认知行为疗法任务表现评估
Nathan Hodson,Simon Williamson
Nathan Hodson
The advent of large language models (LLMs) such as ChatGPT has potential implications for psychological therapies such as cognitive behavioral therapy (CBT). We systematically investigated whether LLMs could recognize an unhelpful thought, ...
Optimizing Clinical Trial Eligibility Design Using Natural Language Processing Models and Real-World Data: Algorithm Development and Validation [0.03%]
基于自然语言处理模型和真实世界数据优化临床试验入组设计：算法研发与验证
Kyeryoung Lee,Zongzhi Liu,Yun Mai et al.
Kyeryoung Lee et al.
Background: Clinical trials are vital for developing new therapies but can also delay drug development. Efficient trial data management, optimized trial protocol, and accurate patient identification are critical for reduc...