Time-series Machine Learning Models to Support Emergency Department Operational Planning [0.03%]
支持急诊科运营规划的时间序列机器学习模型
Tamanna T K Munia,Kyle Marshall,Kitae Kim et al.
Tamanna T K Munia et al.
Predicting emergency department (ED) utilization can assist in resource planning like staff scheduling. Traditional time series methods and newer machine learning methods have been used to forecast ED metrics; however, they have seldom been...
Building a Consumer Health Informatics Introductory Course Consensus Curriculum: An eDelphi Study [0.03%]
基于e德尔菲法的消费者健康信息学入门课程共识性教学大纲的构建研究
Olivia F Krol,Khaya Clark,Vishala Mishra et al.
Olivia F Krol et al.
Digital health technology is becoming increasingly sophisticated and prevalent in modern healthcare. Consumer health informatics (CHI) introductory courses provide a baseline proficiency on this important topic, yet there are no standardize...
Navigating Variability in Prostate RT Planning: Real-Time Insights for Human-Centered CDS Design [0.03%]
前列腺放疗计划中变异性的实时洞察及其在以人为中心的决策支持系统设计中的应用探讨
Meagan Foster,Elizabeth Byrd,Elizabeth Kwong et al.
Meagan Foster et al.
Clinical variability in prostate radiation therapy (RT) planning is well documented, but little is known about how radiation oncologists experience and adapt to the factors that drive it. This study explores variability as a human-centered ...
REPEAT BP: Reviewing Effective Practices for Elevating Adherence in Treatment of Hypertension [0.03%]
重复BP：回顾有效实践以提高高血压治疗依从性的方法
Kevin Ly,Seneca Harberger,Alexander Chang et al.
Kevin Ly et al.
We report on the implementation of an evidence-based program for improving blood pressure (BP) control-the American Medical Association's MAP framework-across an integrated health system with almost 400 primary care providers. We developed ...
Machine Learning for Predicting Drug Release Behavior of PLGA Microspheres [0.03%]
基于PLGA微球的药物释放行为预测的机器学习研究
Andrew F Catapano,Ling Zheng,Xudong Yuan et al.
Andrew F Catapano et al.
PLGA microspheres are widely used in long-acting drug formulations due to their ability to provide sustained release, improving patient adherence and reducing dosing frequency. However, drug release behavior is influenced by complex formula...
Right Patient, Right Specialist, Right Time: Retrieval Augmented Generation for Specialty Referral Routing [0.03%]
合适的患者、合适的专科医师、合适的时间——用于转诊 routing 的检索增强式生成模型
Fateme Nateghi Haredasht,Ethan Goh,Vishnu Ravi et al.
Fateme Nateghi Haredasht et al.
We present an embedding-based retrieval system that automatically directs physician clinical questions to the most relevant specialist-curated question template, which is necessary for the specialist to provide a clinically relevant respons...
No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism [0.03%]
无需黑盒模型：利用时间特征交叉注意机制揭秘临床预测建模
Yubo Li,Xinyu Yao,Rema Padman
Yubo Li
Despite the outstanding performance of deep learning models in clinical prediction tasks, explainability remains a significant challenge. Inspired by transformer architectures, we introduce the Temporal-Feature Cross Attention Mechanism (TF...
Implementation and Assessment of Machine Learning Models for Forecasting Suspected Opioid Overdoses in Emergency Medical Services Data [0.03%]
基于急救服务数据的机器学习模型预测疑似阿片类药物过量的应用与评估
Aaron D Mullen,Daniel R Harris,Peter Rock et al.
Aaron D Mullen et al.
We present efforts in the fields of machine learning and time series forecasting to accurately predict counts of future suspected opioid overdoses recorded by Emergency Medical Services (EMS) in the state of Kentucky. Forecasts help governm...
Refining Substance Use Classification: An Ontological Framework for Enhancing Large-Scale Data Collection [0.03%]
完善物质使用分类：增强大规模数据收集的本体框架
Chi-Hua Lu,Kenneth E Leonard,Werner Ceusters
Chi-Hua Lu
Substance use disorders (SUD) remain prevalent in the United States. The Office of Addiction Services and Support plays a critical role in tracking SUD trends in New York State and reports data to the federal system. However, ambiguities in...
Shifting Information Needs in Clinical Practice: The Evolving Role of Generative AI in Addressing Clinician Demands for Context-Specific Knowledge [0.03%]
临床实践中的信息需求变化：生成式人工智能在满足临床医生特定情境知识需求方面的作用演变
Sachleen K Tuteja,Elise L Boventer,Abdulaziz Alkattan et al.
Sachleen K Tuteja et al.
This study explores clinicians' evolving information needs and evaluates the potential of Generative Artificial Intelligence (Gen AI) to address these gaps by reassessing and extending the Currie et al. (2003) taxonomy. Despite advancements...