Humans and Large Language Models in Clinical Decision Support: A Study with Medical Calculators [0.03%]
人类与大型语言模型在临床决策支持中的应用研究——以医学计算器为例
Nicholas C Wan,Qiao Jin,Joey Chan et al.
Nicholas C Wan et al.
Although large language models (LLMs) have been assessed for general medical knowledge using licensing exams, their ability to support clinical decision-making, such as selecting medical calculators, remains uncertain. We assessed nine LLMs...
Detection of Youth Suicide Interventions in Clinical Record Text using an Open-Source Language Model [0.03%]
基于开源语言模型的临床记录文本中的青少年自杀干预检测方法研究
Juliet B Edgcomb,Alexandra Klomhaus,Joshua Lee et al.
Juliet B Edgcomb et al.
This study presents an automated approach to detect youth suicide prevention interventions documented in emergency department notes. Expert review classified four interventions across 1,794 notes from 200 emergency visits for suicidality am...
Automating Lung-RADS Categorization And Follow-Up Recommendations Using In-Context Learning With Large Language Models [0.03%]
使用大规模语言模型进行上下文学习以自动化肺癌风险分类和随访建议
Tiancheng Zhou,Aokun Chen,Yu Hu et al.
Tiancheng Zhou et al.
Lung cancer remains a significant challenge in public health, ranking among the leading causes of cancer-related mortality. Low-dose computed tomography (LDCT) -based lung cancer screening has emerged as an effective tool for early detectio...
Md Rahat Shahriar Zawad,Irene Y Chen,Peter Washington
Md Rahat Shahriar Zawad
While multiple types of biases can occur in clinical machine learning, the status quo in algorithmic debiasing is to optimize a single fairness metric in the training procedure. We propose a multi-adversarial debiasing framework that builds...
Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence [0.03%]
利用人工智能向在线病人病例推荐临床试验
Joey Chan,Qiao Jin,Nicholas Wan et al.
Joey Chan et al.
Clinical trials are crucial for assessing new treatments; however, recruitment challenges-such as limited awareness, complex eligibility criteria, and referral barriers-hinder their success. With the growth of online platforms, patients, ca...
Metabolic Monitoring among Patients with Type 2 Diabetes Prescribed Second Generation Antipsychotics [0.03%]
二甲双胍用于二代抗精神病药处方患者的代谢监测
Jiali Guo,Jithin Sam Varghese
Jiali Guo
Annual metabolic monitoring is strongly recommended for patients with type 2 diabetes (T2D) prescribed second-generation antipsychotics (SGA). Our objective was to study the rates of monitoring and control in the period after index SGA pres...
Bias Evaluation and Mitigation in Retrieval-Augmented Medical Question-Answering Systems [0.03%]
基于检索的医学问答系统中的偏差评估与缓解
Yuelyu Ji,Hang Zhang,Yanshan Wang
Yuelyu Ji
Medical Question-Answering (QA) systems based on Retrieval-Augmented Generation (RAG) are promising for clinical decision support due to their capability to integrate external knowledge, thus reducing inaccuracies inherent in standalone lar...
When Patients Go to "Dr. Google" Before They Go to the Emergency Department [0.03%]
患者在前往急诊室之前会先咨询"谷歌博士"吗？
Michael A Grasso,Alexandra Rogalski,Naveed Farrukh et al.
Michael A Grasso et al.
Approximately one-third of adults search the internet for health information before visiting an emergency department (ED), with 75% encountering inaccurate content. This study examineshow such searches influence patient care. We conducted a...
Observational Study
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2025 May 22:2024:376-382. DOI: 2025
Unpacking Situational Awareness in Emergency Medical Services: An Eye-Tracking Study of Visual Attention [0.03%]
基于眼动的急诊医学中情境意识的视觉注意力研究
Enze Bai,Zhan Zhang,Kathleen Adelgais et al.
Enze Bai et al.
Situational awareness (SA) is critical for Emergency Medical Services (EMS) providers as they operate in high-stakes, dynamic environments requiring rapid information processing and decision-making. While prior research has explored SA chal...
Interpretable Machine Learning to Identify Risk Factors for Recidivism in Intimate Partner Violence [0.03%]
可解释机器学习在亲密伴侣暴力累犯风险因素识别中的应用
Çeragğ Ogğuztüzün,Mehmet Koyutürk,Günnur Karakurt
Çeragğ Ogğuztüzün
Intimate Partner Violence (IPV) remains a significant global health issue with severe consequences ranging from physical injury to death, with rates rising in recent years. Prediction of recidivism is critical for prevention and treatment. ...