Evaluating short-term forecast accuracy across COVID-19 waves using penalized spline models [0.03%]
使用惩罚样条模型评估新冠肺炎疫情期间短期预测准确性
Nere Larrea,Dae-Jin Lee,Irantzu Barrio et al.
Nere Larrea et al.
Background: During the COVID-19 pandemic, one of the key objectives was to provide daily information on the evolution of the disease. The aim of this study is to evaluate whether the modelling approach used in our area to...
Enhancing stroke recovery assessment: A machine learning approach to real-world hand function analysis [0.03%]
利用机器学习增强卒中恢复评估：真实世界手功能分析方法
Janmesh Ukey,Christian Rogers,Scott Uhlrich et al.
Janmesh Ukey et al.
Background: Hand weakness is a major contributor to long-term disability in stroke survivors, severely affecting daily function and quality of life. Although wrist-worn accelerometers offer an objective means of measuring...
The value of machine and deep learning in management of critically ill patients: An umbrella review [0.03%]
重症患者管理中机器学习和深度学习的价值：伞式综述
Meiram Tungushpayev,Diana Suleimenova,Antonio Sarria-Santamerra et al.
Meiram Tungushpayev et al.
Objective: The integration of Artificial Intelligence and Machine Learning methods in healthcare, particularly in Intensive Care Units (ICUs), has great potential to transform medical care. This umbrella systematic review...
Development and validation of a machine learning-based prediction model for in-ICU mortality in severe pneumonia: A dual-center retrospective study [0.03%]
基于机器学习的重症肺炎患者ICU内死亡预测模型的开发与验证：一项双中心回顾性研究
JunYing Niu,XiaoJie Lv,Lin Gao et al.
JunYing Niu et al.
Introduction: Severe pneumonia (SP) carries a high risk of death in the intensive care unit (ICU). There is a paucity of effective assessment tools for ICU mortality in clinical practice. Therefore, this dual-centre study...
Victor Vadmand Jensen,Marianne Johansson Jørgensen,Rikke Hagensby Jensen et al.
Victor Vadmand Jensen et al.
Introduction: Nations are increasingly turning towards artificial intelligence (AI) systems to support healthcare settings. While nations must then contend with ethical considerations surrounding healthcare AI, they do so...
Impact of artificial intelligence on hospital admission prediction and flow optimization in health services: a systematic review [0.03%]
人工智能在卫生服务中的影响：基于系统评价的医院入院预测及流程优化
Aline Lucas Nunes,Thiago Lisboa,Bruna Nichele da Rosa et al.
Aline Lucas Nunes et al.
Background: Artificial Intelligence (AI)-assisted prediction of hospital admission is an innovative tool that optimizes resource allocation and improves patient flow within emergency departments. Health institutions need ...
Enhan Liu,Zhengqian Jiang,Zihang Wang et al.
Enhan Liu et al.
Objectives: To tackle the challenge of noise in grayscale electrocardiograms (ECGs) transcribed from paper records, this study proposes a Generative Adversarial Networks (GANs)-based framework that includes both a denoisi...
Development and validation of an interpretable machine learning model for cerebral small vessel disease risk assessment [0.03%]
一种用于脑小血管疾病风险评估的可解释机器学习模型的研发与验证
Tao Guo,Mengchen Wang,Changliang Wang et al.
Tao Guo et al.
Objective: Given the limited accessibility of magnetic resonance imaging (MRI) for diagnosing cerebral small vessel disease (CSVD) in community settings and the lack of practical early risk assessment tools, we aimed to d...
AI-based assessment of pulmonology inpatient consultation note completeness: predicting documentation gaps and response delays [0.03%]
基于人工智能的肺科住院会诊记录完整性的评估：预测文档缺口及回应延迟
Damla Azakli Yazici,Celal Satici,Ayse Bahadir et al.
Damla Azakli Yazici et al.
Objectives: Inpatient consultation notes frequently suffer from incomplete documentation, which may delay clinical decision-making and compromise patient care. Although consultations are central to multidisciplinary coord...
"Terrible Stuff. We've been had": hospital staff reactions to a new electronic health record and implications for employee well-being - A qualitative study [0.03%]
“太糟糕了。上当受骗了”——医务人员对于新的电子健康记录系统的反应及其对员工健康的启示- 定量研究
Eivind Sæthre,Solveig Osborg Ose,Steinar Krokstad et al.
Eivind Sæthre et al.
Background: Electronic Health Record (EHR) implementations significantly affect healthcare professionals' work routines. Previous Epic implementations in Scandinavian hospitals have led to negative outcomes, highlighting ...