Acceptability and perceived usefulness of the CHAMPS intervention for improving medication adherence among people with HIV in Alabama and New York [0.03%]
美国阿拉巴马州和纽约州艾滋病患者改善CHAMPS干预措施用药依从性的可接受性和有用性感知程度
Maeve Brin,Claudia Michaels,Patrick Veihman et al.
Maeve Brin et al.
Background: Antiretroviral therapy allows people with HIV to manage the disease as a chronic illness rather than a fatal diagnosis as regular adherence can lead to viral suppression. It is estimated, however, that less th...
Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach [0.03%]
机器学习方法预测功能性便秘患者出现便血的营养和生活方式危险因素分析
Joyeta Ghosh,Jyoti Taneja,Ravi Kant
Joyeta Ghosh
Background: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifestyle habits. Early identification of at-risk individuals through machine ...
"Simplification, decentralization, proximity" - A critical analysis of the digital health framework in Portugal through expert interviews [0.03%]
“简化、去中心化、贴近民众”——通过专家访谈剖析葡萄牙的数字健康框架
Marta Estrela,Pedro Lopes Ferreira,Fátima Roque et al.
Marta Estrela et al.
Introduction: The implementation of digital health tools and services encounters policy and governance challenges tied to a complex web of stakeholders and influencing factors. This study seeks analyse the digital health ...
Utilizing machine learning for predicting mortality in patients with heat-related illness who visited the emergency department [0.03%]
利用机器学习预测中暑急诊患者的死亡率
Wan-Yin Kuo,Chien-Cheng Huang,Chung-Feng Liu et al.
Wan-Yin Kuo et al.
Background: In the context of climate change and global warming, heat-related illness (HRI) is anticipated to escalate and become a major concern. Patients with severe HRI primarily present to the emergency department (ED...
Patient-reported usability challenges when implementing integrated EHR medication reminders for kidney transplant patients in a home setting: A pilot study [0.03%]
肾脏移植患者家中实施集成电子健康病历药物提醒时患者的使用挑战：一项初步研究
S J Oudbier,J W Aarts,J M Kloes van der et al.
S J Oudbier et al.
Background: With an aging population and the increasing prevalence of chronic diseases such as chronic kidney disease (CKD), kidney transplantation is the preferred treatment for end-stage renal disease due to its superio...
Evaluating the impact of explainable AI on clinicians' decision-making: A study on ICU length of stay prediction [0.03%]
可解释人工智能对临床医生决策影响的评估：一项重症监护病房住院时间预测研究
Jinsun Jung,Sunghoon Kang,Jeeyae Choi et al.
Jinsun Jung et al.
Background: Explainable Artificial Intelligence (XAI) is increasingly vital in healthcare, where clinicians need to understand and trust AI-generated recommendations. However, the impact of AI model explanations on clinic...
"I don't know": An uncertainty-aware machine learning model for predicting patient disposition at emergency department triage [0.03%]
“我不知道”：一种不确定性的机器学习模型，用于预测急诊分诊患者的去向
Abubakar Sadiq Bouda Abdulai,Jean Storm,Michael Ehrlich
Abubakar Sadiq Bouda Abdulai
Background: Machine learning (ML) models are widely used for predicting patient disposition at emergency department (ED) triage. However, these models generate predictions regardless of the level of uncertainty, potential...
Ontology accelerates few-shot learning capability of large language model: A study in extraction of drug efficacy in a rare pediatric epilepsy [0.03%]
本体加速大型语言模型的少样本学习能力：一种罕见儿童癫痫药物疗效提取的研究
Pedram Golnari,Katrina Prantzalos,Veronica Hood et al.
Pedram Golnari et al.
Objective: Dravet Syndrome (DS) is a developmental and epileptic encephalopathy that is characterized by severe, prolonged motor seizures and high resistance to multiple antiseizure medications (ASMs) with multiple comorb...
Interface design features of clinical decision support systems for real-time detection of deterioration: A scoping review [0.03%]
临床决策支持系统实时检测病情恶化的界面设计特点：一项概要性审查
Tamasha Jayawardena,Melissa Baysari,Adeola Bamgboje-Ayodele
Tamasha Jayawardena
Background: Clinical decision support systems (CDSS) can support clinicians with the timely detection of patients' clinical deterioration, however, less than half of clinical decision support (CDS) systems implemented for...
Using longitudinal data and deep learning models to enhance resource allocation in home-based medical care [0.03%]
利用纵向数据和深度学习模型改进居家医疗服务资源配置
Ling Chen,Ching-Po Lin,Chi-Hua Chung et al.
Ling Chen et al.
Background: The aging population is driving increased healthcare demands and costs, prompting the need for effective home healthcare programs. Accurate patient assessment is essential for optimizing resource allocation an...