Identifying New Risk Associations Between Chronic Physical Illness and Mental Health Disorders in China: Machine Learning Approach to a Retrospective Population Analysis [0.03%]
在中国识别慢性躯体疾病与精神健康障碍之间的新风险关联：一种面向人口的回顾性分析的机器学习方法
Lizhong Liang,Tianci Liu,William Ollier et al.
Lizhong Liang et al.
Background: The mechanisms underlying the mutual relationships between chronic physical illnesses and mental health disorders, which potentially explain their association, remain unclear. Furthermore, how patterns of this...
Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study [0.03%]
基于电子健康记录利用混合型自然语言处理方法在大型综合医疗体系中识别哮喘相关症状的回顾性研究
Fagen Xie,Robert S Zeiger,Mary Marycania Saparudin et al.
Fagen Xie et al.
Background: Asthma-related symptoms are significant predictors of asthma exacerbation. Most of these symptoms are documented in clinical notes in a free-text format, and effective methods for capturing asthma-related symp...
Large Language Models for Thematic Summarization in Qualitative Health Care Research: Comparative Analysis of Model and Human Performance [0.03%]
大型语言模型在定性医疗保健研究主题摘要中的应用：模型与人工性能比较分析
Arturo Castellanos,Haoqiang Jiang,Paulo Gomes et al.
Arturo Castellanos et al.
Background: The application of large language models (LLMs) in analyzing expert textual online data is a topic of growing importance in computational linguistics and qualitative research within health care settings. ...
Using Segment Anything Model 2 for Zero-Shot 3D Segmentation of Abdominal Organs in Computed Tomography Scans to Adapt Video Tracking Capabilities for 3D Medical Imaging: Algorithm Development and Validation [0.03%]
利用片段任何模型2对计算机断层扫描图像中的腹部器官进行零样本三维分割以适应视频跟踪能力的三维医学成像：算法开发与验证
Yosuke Yamagishi,Shouhei Hanaoka,Tomohiro Kikuchi et al.
Yosuke Yamagishi et al.
Background: Medical image segmentation is crucial for diagnosis and treatment planning in radiology, but it traditionally requires extensive manual effort and specialized training data. With its novel video tracking capab...
Evaluation of ChatGPT Performance on Emergency Medicine Board Examination Questions: Observational Study [0.03%]
ChatGPT在急诊医学执业考试试题上的表现评估：观察性研究
Mila Pastrak,Sten Kajitani,Anthony James Goodings et al.
Mila Pastrak et al.
Background: The ever-evolving field of medicine has highlighted the potential for ChatGPT as an assistive platform. However, its use in medical board examination preparation and completion remains unclear. ...
Leveraging Large Language Models for Accurate Retrieval of Patient Information From Medical Reports: Systematic Evaluation Study [0.03%]
利用大型语言模型从医学报告中准确检索患者信息的系统性评价研究
Angel Manuel Garcia-Carmona,Maria-Lorena Prieto,Enrique Puertas et al.
Angel Manuel Garcia-Carmona et al.
Background: The digital transformation of health care has introduced both opportunities and challenges, particularly in managing and analyzing the vast amounts of unstructured medical data generated daily. There is a need...
Comparative Performance of Medical Students, ChatGPT-3.5 and ChatGPT-4.0 in Answering Questions From a Brazilian National Medical Exam: Cross-Sectional Questionnaire Study [0.03%]
比较医学生、ChatGPT-3.5和ChatGPT-4.0回答巴西国家医学考试试题的表现：横断面问卷调查研究
Mateus Rodrigues Alessi,Heitor Augusto Gomes,Gabriel Oliveira et al.
Mateus Rodrigues Alessi et al.
Background: Artificial intelligence has advanced significantly in various fields, including medicine, where tools like ChatGPT (GPT) have demonstrated remarkable capabilities in interpreting and synthesizing complex medic...
Performance of 3 Conversational Generative Artificial Intelligence Models for Computing Maximum Safe Doses of Local Anesthetics: Comparative Analysis [0.03%]
三种会话式生成型人工智能模型计算局部麻醉药最大安全剂量的性能比较分析
Mélanie Suppan,Pietro Elias Fubini,Alexandra Stefani et al.
Mélanie Suppan et al.
Background: Generative artificial intelligence (AI) is showing great promise as a tool to optimize decision-making across various fields, including medicine. In anesthesiology, accurately calculating maximum safe doses of...
Correction: Striking a Balance: Innovation, Equity, and Consistency in AI Health Technologies [0.03%]
关于“把握平衡：AI医疗技术领域的创新、公平与一致性”的更正通知
Eric Perakslis,Kimberly Nolen,Ethan Fricklas et al.
Eric Perakslis et al.
The Elastic Electronic Health Record: A Five-Tiered Framework for Applying Artificial Intelligence to Electronic Health Record Maintenance, Configuration, and Use [0.03%]
弹性电子健康记录：应用人工智能进行电子病历维护、配置和使用的五层框架
Colby Uptegraft,Kameron Collin Black,Jonathan Gale et al.
Colby Uptegraft et al.
Properly configuring modern electronic health records (EHRs) has become increasingly challenging for human operators, failing to fully meet the efficiency and cost-saving potential seen with the digitization of other sectors. The integratio...