The pneumonia severity index: Assessment and comparison to popular machine learning classifiers [0.03%]
肺炎严重程度指数评估及与流行机器学习分类器的比较
Dawei Wang,Deanna R Willis,Yuehwern Yih
Dawei Wang
Introduction: Pneumonia is the top communicable cause of death worldwide. Accurate prognostication of patient severity with Community Acquired Pneumonia (CAP) allows better patient care and hospital management. The Pneumo...
The electronic prescribing of subcutaneous infusions: A before-and-after study assessing the impact upon patient safety and service efficiency [0.03%]
电子处方皮下输液：一项关于对患者安全及服务效率影响的前后研究
Jonathan Hindmarsh,Keith Holden
Jonathan Hindmarsh
Objectives: To assess the impact of electronically prescribed mixed-drug infusions on the prevalence and types of prescription errors and staff time. Desi...
Improving morbidity information in Portugal: Evidence from data linkage of COVID-19 cases surveillance and mortality systems [0.03%]
利用数据关联改善葡萄牙的疾病信息——来自COVID-19病例监测和死亡系统证据
Rodrigo Feteira-Santos,Catarina Camarinha,Miguel de Araújo Nobre et al.
Rodrigo Feteira-Santos et al.
Background: COVID-19 rapidly spread around the world, putting health systems under unprecedented pressure and continuous adaptations. Well-established health information systems (HIS) are crucial in providing data to allo...
From Personal Observations to Recommendation of Tailored Interventions based on Causal Reasoning: a case study of Falls Prevention in Elderly Patients [0.03%]
从个人观察到基于因果推理的个性化干预建议：老年人跌倒预防案例研究
Salma Chaieb,Ali Ben Mrad,Brahim Hnich
Salma Chaieb
Objective: While the challenge of estimating the efficacy of therapies using observational data has received a lot of attention, little work has been done on estimating the treatment effect from interventions. In this pap...
Measuring the cost-effectiveness of using telehealth for diabetes management: A narrative review of methods and findings [0.03%]
糖尿病管理使用远程医疗的成本效益评价：方法和结果的叙事性回顾
Ofir Ben-Assuli
Ofir Ben-Assuli
Introduction: Diabetes is a chronic metabolic disease characterized by high levels of blood glucose, which can lead over time to severe impairment to the heart, blood vessels, eyes, kidneys, nerves and premature death. Di...
Logistic regression models for patient-level prediction based on massive observational data: Do we need all data? [0.03%]
基于大规模观察数据的患者水平预测逻辑回归模型：我们需要所有数据吗？
Luis H John,Jan A Kors,Jenna M Reps et al.
Luis H John et al.
Objective: Provide guidance on sample size considerations for developing predictive models by empirically establishing the adequate sample size, which balances the competing objectives of improving model performance and r...
Frequency of use and preferences for information and communication technologies in patients with sleep apnea: A multicenter, multinational, observational cross-sectional survey study [0.03%]
睡眠呼吸暂停患者使用信息和通信技术的频率和偏好：一项多中心、多国、观察性横断面调查研究
Veronica R Jaritos,Emanuel Vanegas,Juan Facundo Nogueira et al.
Veronica R Jaritos et al.
Background: Obstructive sleep apnea (OSA) is a condition characterized by repeated episodes of partial or complete obstruction of the upper airway during sleep. An accessible method to facilitate self-management education...
Effectiveness of a web-based, electronic medical records-integrated patient agenda tool to improve doctor-patient communication in primary care consultations: A pragmatic cluster-randomized controlled trial study [0.03%]
一种基于网络的、与电子病历整合的以患者为中心的日程工具能改善基层医疗中的医患交流吗？一项务实的整体式随机对照试验研究
Yew Kong Lee,Chirk Jenn Ng,Mohamed Reza Syahirah et al.
Yew Kong Lee et al.
Background: Doctors may struggle to identify patient agendas during busy primary care consultations. Therefore, an online patient agenda tool (the Values in Shared Interactions Tool- VISIT) was developed which allowed pat...
Randomized Controlled Trial
International journal of medical informatics. 2022 Jun:162:104761. DOI:10.1016/j.ijmedinf.2022.104761 2022
Binary acronym disambiguation in clinical notes from electronic health records with an application in computational phenotyping [0.03%]
基于电子健康记录中的临床笔记进行二元首字母词消歧及在表型计算中的应用
Nicholas B Link,Sicong Huang,Tianrun Cai et al.
Nicholas B Link et al.
Objective: The use of electronic health records (EHR) systems has grown over the past decade, and with it, the need to extract information from unstructured clinical narratives. Clinical notes, however, frequently contain...
Machine learning models for diabetes management in acute care using electronic medical records: A systematic review [0.03%]
基于电子病历的急性期糖尿病管理的机器学习模型系统评价研究
Amir Kamel Rahimi,Oliver J Canfell,Wilkin Chan et al.
Amir Kamel Rahimi et al.
Background: Machine learning (ML) is a subset of Artificial Intelligence (AI) that is used to predict and potentially prevent adverse patient outcomes. There is increasing interest in the application of these models in di...