Benchmarking of pre-training strategies for electronic health record foundation models [0.03%]
电子健康记录基础模型预训练策略的基准测试
Samson Mataraso,Shreya D&#x;Souza,David Seong et al.
Samson Mataraso et al.
Objective: Our objective is to compare different pre-training strategies for electronic health record (EHR) foundation models. Materials and methods: ...
Ensemble learning to enhance accurate identification of patients with glaucoma using electronic health records [0.03%]
基于电子健康记录的机器学习方法鉴别青光眼患者准确性研究
Tushar Mungle,Behzad Naderalvojoud,Chris A Andrews et al.
Tushar Mungle et al.
Objectives: Existing ophthalmology studies for clinical phenotypes identification in real-world datasets (RWD) rely exclusively on structured data elements (SDE). We evaluated the performance, generalizability, and fairne...
Subpopulation-specific synthetic electronic health records can increase mortality prediction performance [0.03%]
特定亚群体的人工智能合成电子健康病历可以提高死亡率预测的准确性
Oriel Perets,Nadav Rappoport
Oriel Perets
Objective: To address biased representation in Electronic Health Records (EHRs) across subpopulations (SPs), which leads to predictive models underperforming for underrepresented groups, we propose a framework to enhance ...
A community-based approach to ethical decision-making in artificial intelligence for health care [0.03%]
面向医疗保健的人工智能的社区伦理决策方法
Abdou S Senghor,Tiffani J Bright,Saya Kakim et al.
Abdou S Senghor et al.
Objectives: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment recommendations, and resource allocation. However, its implementation also raises ethical concerns, particularly rega...
Measurement, drivers, and outcomes of patient-initiated secure messaging use and intensity: a scoping review [0.03%]
基于患者的安全部署消息使用和强度的测量、驱动因素及结果：综述研究
Aleksandra Wec,Kelly T Gleason,Danielle Peereboom et al.
Aleksandra Wec et al.
Objective: Use of secure messaging through the patient portal has increased in recent years. We compile evidence of how patient-initiated secure messaging has been measured, factors associated with use, and effects on ind...
Evaluating prompt and data perturbation sensitivity in large language models for radiology reports classification [0.03%]
大型语言模型在放射学报告分类中的提示和数据扰动敏感性评估
Vera Sorin,Jeremy D Collins,Alex K Bratt et al.
Vera Sorin et al.
Objectives: Large language models (LLMs) offer potential in natural language processing tasks in healthcare. Due to the need for high accuracy, understanding their limitations is essential. The purpose of this study was t...
Chronic obstructive pulmonary disease screening using time-frequency features of self-recorded respiratory sounds [0.03%]
基于自我记录呼吸音的时间频率特性进行慢性阻塞性肺病筛查
Alberto Tena,Ivan Juez-Garcia,Iván D Benítez et al.
Alberto Tena et al.
Objectives: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, with up to 70% of cases remaining undiagnosed. This paper proposes a COPD screening tool based on time-frequency repr...
Forecasting school violence risk with incomplete interview data: an automated assessment approach [0.03%]
利用不完整访谈数据预测学校暴力风险：自动评估方法
Lara J Kanbar,Alexander Osborn,Andrew Cifuentes et al.
Lara J Kanbar et al.
Objectives: School violence risk prevention in the United States relies on manual assessments that are time-consuming and subjective. We developed a machine learning algorithm named Automated RIsk Assessment (ARIA), using...
VetDash: a clinical dashboard for enhancing measurement-based care in veteran health [0.03%]
基于测量的护理老兵健康临床显示屏：VetDash应用程序
Santiago Allende,Hayley S Sullivan,Peter J Bayley
Santiago Allende
Objectives: Measurement-based care (MBC) improves clinical decision-making but remains underutilized in the Veterans Health Administration due to barriers such as provider awareness, time constraints, and user-experience ...
Explaining care need assessment surveys: qualitative and quantitative evaluation of state-of-the-art local and global explainable artificial intelligence methods [0.03%]
护理需求评估调查的解释：局部和全局可解释人工智能方法的状态-of-艺术定性和定量评价
Necip Oğuz Şerbetci,Stefan Blüher,Paul Gellert et al.
Necip Oğuz Şerbetci et al.
Objective: With extended life expectancy, the number of people in need of care has been growing. To optimally support them, it is important to know the patterns and conditions of their daily life that influence the need f...