EHR-ML: A data-driven framework for designing machine learning applications with electronic health records [0.03%]
基于电子健康记录的机器学习应用的数据驱动设计框架
Yashpal Ramakrishnaiah,Nenad Macesic,Geoffrey I Webb et al.
Yashpal Ramakrishnaiah et al.
Objective: The healthcare landscape is experiencing a transformation with the integration of Artificial Intelligence (AI) into traditional analytic workflows. However, its integration faces challenges resulting in a crisi...
Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records [0.03%]
基于深度学习的区域电子健康记录在2型糖尿病患者抑郁症和焦虑症预测中的应用
Wei Feng,Honghan Wu,Hui Ma et al.
Wei Feng et al.
Background: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to ful...
Hip prosthesis failure prediction through radiological deep sequence learning [0.03%]
基于放射学的深度序列学习的髋关节假体失败预测
Francesco Masciulli,Anna Corti,Alessia Lindemann et al.
Francesco Masciulli et al.
Background: Existing deep learning studies for the automated detection of hip prosthesis failure only consider the last available radiographic image. However, using longitudinal data is thought to improve the prediction, ...
Optimal placement of ambulance stations using data-driven direct and surrogate search methods [0.03%]
基于数据驱动的直接和替代搜索方法的救护车站点最优布置
Hassan Bozorgmanesh,Patrik Rydén
Hassan Bozorgmanesh
Objective: In this paper, we implement and validate a set of optimization approaches that were applied on ambulance data from the Västerbotten county in Sweden collected 2018, with the objective to find the optimal place...
Artificial intelligence-enabled obesity prediction: A systematic review of cohort data analysis [0.03%]
基于人群数据的人工智能肥胖预测方法系统性综述研究
Sharareh Rostam Niakan Kalhori,Farid Najafi,Hajar Hasannejadasl et al.
Sharareh Rostam Niakan Kalhori et al.
Background: Obesity, now the fifth leading global cause of death, has seen a dramatic rise in prevalence over the last forty years. It significantly increases the risk of diseases such as type 2 diabetes and cardiovascula...
Shan Chen,Yuanzhao Ding
Shan Chen
Background: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has b...
Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records [0.03%]
基于深度学习和电子健康记录的抗中性粒细胞胞浆抗体相关血管炎队列识别
Liqin Wang,John Novoa-Laurentiev,Claire Cook et al.
Liqin Wang et al.
Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep lea...
Enhancing information for action: A strategic tool for strengthening public health emergency management systems [0.03%]
行动导向的信息强化：加强公共卫生应急管理体系的战略工具
Catherine Smallwood,Carlos Matos,Hugo Monteiro et al.
Catherine Smallwood et al.
Background: This paper addresses the importance of timely and robust information systems that underpin emergency response decision-making, as evidenced during the COVID-19 pandemic in the WHO European Region. Recognizing ...
Behind the software: The impact of Unobtrusiveness, Goal Setting and persuasive features on BMI [0.03%]
减肥软件背后的因素：低调性、目标设定和说服性功能对BMI的影响
Renata Savian Colvero de Oliveira,Sharon Nabwire,Heta Merikallio et al.
Renata Savian Colvero de Oliveira et al.
Background: Studies have demonstrated that interventions targeting weight loss and body mass index (BMI) reduction can be successful, although the specific factors that influence their effectiveness are still unclear. Beh...
Public value and digital health: The example of guiding values in the national digital health strategy of France [0.03%]
数字健康中的公共价值：以法国国家数字健康战略为例
Simon Lewerenz,Anne Moen,Henrique Martins
Simon Lewerenz
Introduction: In the WHO European Region, 44 of 53 reporting Member States (MS) have a national digital health strategy (NDHS) or policy. Their formulation is heterogenous and evolving and should best reflect public commo...