Augmenting large language models to predict social determinants of mental health in opioid use disorder using patient clinical notes [0.03%]
利用患者临床记录增强大型语言模型以预测阿片类药物使用障碍中的心理健康社会决定因素
Madhavi Pagare,Deva Sai Kumar Bheesetti,Inyene Essien-Aleksi et al.
Madhavi Pagare et al.
Objective: Identifying social determinants of mental health (SDOMH) in patients with opioid use disorder (OUD) is crucial for estimating risk and enabling early intervention. Extracting such data from unstructured clinica...
Artificial intelligence-generated draft replies to patient messages in pediatrics [0.03%]
儿科患者消息的人工智能生成草稿回复
April S Liang,Shivam Vedak,Alex Dussaq et al.
April S Liang et al.
Objectives: This study describes the utilization and experiences of artificial intelligence (AI)-generated draft responses to patient messages in pediatric ambulatory clinicians and contextualizes their experiences in rel...
Using large language models for temporal relation extraction from pediatric clinical reports [0.03%]
利用大型语言模型从儿科临床报告中提取时间关系
Judith Jeyafreeda Andrew,Juliette Potier,Nicolas Garcelon et al.
Judith Jeyafreeda Andrew et al.
Objectives: To evaluate large language models (LLMs) for extracting temporal relations from pediatric rare disease clinical reports to enable automated patient timeline creation. ...
Case Reports
JAMIA open. 2025 Nov 22;8(6):ooaf121. DOI:10.1093/jamiaopen/ooaf121 2025
Synthetic data generation of health and demographic surveillance systems data: a case study in a low- and middle-income country [0.03%]
低收入和中等收入国家卫生和人口监测系统数据的合成数据生成：一项案例研究
Dorcas G Mwigereri,Nigel T Kamotho,Akbar K Waljee et al.
Dorcas G Mwigereri et al.
Objective: To evaluate effectiveness of open-source generative models in producing high-quality tabular synthetic data using a Health and Demographic Surveillance System (HDSS) dataset from rural Kenya, as a proof of conc...
Implementing system-wide digital medical interpretation: a framework for healthcare organizations [0.03%]
实现全系统的数字医疗翻译：医疗机构的实施框架
Ulka Kothari,Allison Squires,Jonathan Austrian et al.
Ulka Kothari et al.
Objectives: This study evaluates and enhances language access services for Limited English Proficiency (LEP) patients in a large urban health system by integrating interpreter services into the Electronic Health Record (E...
Proportion of alcohol use disorder diagnoses in electronic health records documented with stigmatized descriptors: a comparison across race, ethnicity, and sex [0.03%]
电子健康记录中污名化描述的比例：按种族、族裔和性别对比酒精使用障碍诊断比例
Robert L Ellis,Kevin A Hallgren,Emily C Williams et al.
Robert L Ellis et al.
Objectives: In a sample of patients with diagnosed alcohol use disorder (AUD), we examined the prevalence of both stigmatizing (eg, "alcohol abuse") and highly stigmatizing, non-medical descriptors (eg, "alcoholic") docum...
Pablo Guerrero,Morten Ernebjerg,Thomas Holst et al.
Pablo Guerrero et al.
Objective: To present the Artificial Intelligence-Ready Mount Sinai (AIR·MS) platform-unified access to diverse clinical datasets from the Mount Sinai Health System (MSHS), along with computational infrastructure for AI-...
Benchmarking speech-to-text robustness in noisy emergency medical dialogues: an evaluation of models under realistic acoustic conditions [0.03%]
在现实声学条件下评估模型的医疗急救对话中语音转文本的鲁棒性基准测试
Denis Moser,Nikola Stanic,Murat Sariyar
Denis Moser
Objectives: To evaluate the transcription accuracy of 6 German-capable speech-to-text (STT) systems in simulated emergency medical services (EMS) environments, focusing on clinically relevant performance under noisy and m...
Exploring the potential of large language models for assessing medication adherence to the ESC heart failure guidelines [0.03%]
探究大型语言模型在评估心脏病患者用药依从性方面的潜力以遵守欧洲心脏病学会的心力衰竭指南
Noman Dormosh,Machteld Boonstra,Ameen Abu-Hanna et al.
Noman Dormosh et al.
Objective: To evaluate large language models (LLMs) for automating the assessment of clinician adherence to ESC heart failure pharmacotherapy guidelines. ...
The missing link: electronic health record linkage across species offers opportunities for improving One Health [0.03%]
缺失的环节：跨物种电子健康记录链接为改善“同一健康”提供了机会
Kathleen R Mullen,Nadia Saklou,Adam Kiehl et al.
Kathleen R Mullen et al.
Objective: Significant opportunities for understanding the co-occurrence of conditions across species in coincident households remain untapped. We determined the feasibility of creating a Companion Care Registry (CCR) for...