Cluster analysis to identify targeted interventions for highly multimorbid patients in a one-million population in England [0.03%]
聚类分析在英国一百万人口中识别高度多病患者的针对性干预措施
Richard M Wood,Peter M Thomson,Sam T Creavin
Richard M Wood
Whole population segmentation can be a valuable asset to help understand the general distribution of health needs and healthcare utilisation within a population. In the one million resident health system in and around Bristol (UK), existing...
Predicting asthma-related hospitalizations in underserved and rural populations in Algeria [0.03%]
预测阿尔及利亚边缘化和农村人口哮喘相关住院情况
Amin Bouamar,Ghalem Belalem,Boumedyen Belaid et al.
Amin Bouamar et al.
We developed a comprehensive system architecture that incorporates a predictive module for assessing hospitalization risk due to asthma exacerbations. This module is specifically designed to promote equitable access to healthcare services f...
Optimal screening selection rates for post-traumatic stress disorder and the impact of social stigma [0.03%]
创伤后应激障碍的最佳筛查选择率及社会歧视的影响
Gian-Gabriel P Garcia,Navid Ghaffarzadegan,Mohammad S Jalali
Gian-Gabriel P Garcia
Recent interest in optimizing diagnostic thresholds for Post-traumatic Stress Disorder (PTSD) screening tools is motivated by the need to improve diagnostic accuracy and facilitate early treatment of PTSD within high-risk populations. Howev...
Reach: Recognising episodes of acute complexity in health: a predictive older patient prioritisation machine learning model [0.03%]
识别健康状况急性复杂期的预测模型：一种优先处理老年患者的人工智能模型
Abtin Ijadi Maghsoodi,Valery Pavlov,Paul Rouse et al.
Abtin Ijadi Maghsoodi et al.
As the numbers of older people (65 +) rise globally, the pressure on acute hospitals to provide efficient and effective care while addressing resource inequities increases. In this study we introduce Recognising Episodes of Acute Complexity...
An optimization-embedded simulation approach for quantifying the operational impacts of right-sizing prenatal care [0.03%]
一种嵌入式优化仿真方法 用于量化右尺寸产前护理的运营影响
Leena Ghrayeb,Amy Cohn,Ruiwei Jiang et al.
Leena Ghrayeb et al.
The United States spends approximately $111 billion annually on maternity care but has the worst maternal mortality rate among peer high-income nations. Recent studies suggest that outdated prenatal care guidelines may be a cause for this. ...
Improving treatment outcomes in Ghana with agent-based model for diabetes patients' self-management behaviours [0.03%]
基于患者自我管理行为的_agent_模型在改善冈比亚糖尿病治疗效果中的应用
Eunice Twumwaa Tagoe,Justice Nonvignon,Robert Van Der Meer et al.
Eunice Twumwaa Tagoe et al.
Despite universal health coverage policies, diabetes management in resource-constrained settings remains challenging due to complex interactions between patient behaviours and systemic barriers. This study combines health behaviour theories...
Strategic management of vaccine distribution during pandemics under uncertainty [0.03%]
不确定性下的大流行疫苗分配的战略管理
Mahsa Mohammadi,Mohsen Roytvand Ghiasvand,Donya Rahmani et al.
Mahsa Mohammadi et al.
The pandemic has reshaped how supply chain networks (SCNs) are designed, particularly in the context of vaccine distribution. This study introduces a new solution methodology to address the challenges of managing large-scale vaccine supply ...
Cross-training of nurses during a global pandemic: a two-stage stochastic programming approach [0.03%]
全球大流行期间护士的交叉培训：两阶段随机规划方法
Hendrik Winzer,Jens Bengtsson
Hendrik Winzer
During a global pandemic, hospitals face challenges of uncertain patient influx and increased risk of absenteeism among medical personnel, both of which adversely impact patient safety. To address these challenges, we propose a two-stage st...
Data-driven smart freight fleet management amid epidemic disruptions: A framework and case study [0.03%]
疫情扰动下的数据驱动智慧货运车队管理框架与案例研究
Carlos D Paternina-Arboleda,Diana G Ramirez-Rios,Karenina N Zaballa et al.
Carlos D Paternina-Arboleda et al.
This article introduces a comprehensive data-driven framework for intelligent freight fleet management that effectively addresses the challenges presented by epidemic disruptions. By harnessing the power of data analytics and decision-makin...
Improving hard-to-place kidney allocation: A machine learning approach to center ranking [0.03%]
基于机器学习的中心排名以改善难以移植的肾脏分配问题
Sean Berry,Berk Görgülü,Sait Tunç et al.
Sean Berry et al.
Kidney transplantation is the preferred treatment for end-stage renal disease, yet donor scarcity and inefficiencies in allocation systems create major bottlenecks, resulting in prolonged wait times and alarming mortality rates. Despite the...