Evaluating machine learning algorithms to Predict 30-day Unplanned REadmission (PURE) in Urology patients [0.03%]
评估机器学习算法预测泌尿科患者30天内意外再入院(PURE)的效果
Koen Welvaars,Michel P J van den Bekerom,Job N Doornberg et al.
Koen Welvaars et al.
Background: Unplanned hospital readmissions are serious medical adverse events, stressful to patients, and expensive for hospitals. This study aims to develop a probability calculator to predict unplanned readmissions (PU...
Development and usability evaluation of a mHealth application for albinism self-management [0.03%]
用于评估脱色症自我管理的移动健康应用程序的发展和适用性评价
Saman Mortezaei,Reza Rabiei,Farkhondeh Asadi et al.
Saman Mortezaei et al.
Background: Reduced or absence of melanin poses physical, social, and psychological challenges to individuals with albinism. Mobile health (mHealth) applications have the potential to improve the accessibility of informat...
Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study [0.03%]
利用机器学习开发一种用于预测抗抑郁药相关出血的临床模型：一项可行性研究
Jatin Goyal,Ding Quan Ng,Kevin Zhang et al.
Jatin Goyal et al.
Introduction: Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machin...
Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach [0.03%]
一种用于预测再入院的解释型机器学习模型：提取回归树两步法
Xiaoquan Gao,Sabriya Alam,Pengyi Shi et al.
Xiaoquan Gao et al.
Background: Advanced machine learning models have received wide attention in assisting medical decision making due to the greater accuracy they can achieve. However, their limited interpretability imposes barriers for pra...
Developing a mobile health application for wound telemonitoring: a pilot study on abdominal surgeries post-discharge care [0.03%]
一种移动医疗应用的开发在出院后腹部手术切口的远程监控:一次初步研究
Tayebeh Baniasadi,Mehdi Hassaniazad,Sharareh Rostam Niakan Kalhori et al.
Tayebeh Baniasadi et al.
Background: Many early signs of Surgical Site Infection (SSI) developed during the first thirty days after discharge remain inadequately recognized by patients. Hence, it is important to use interactive technologies for p...
Using a decision tree algorithm to distinguish between repeated supra-therapeutic and acute acetaminophen exposures [0.03%]
使用决策树算法区分重复的超治疗性的对乙酰氨基酚中毒和急性对乙酰氨基酚中毒
Omid Mehrpour,Christopher Hoyte,Samaneh Nakhaee et al.
Omid Mehrpour et al.
Background: This study aimed to compare clinical and laboratory characteristics of supra-therapeutic (RSTI) and acute acetaminophen exposures using a predictive decision tree (DT) algorithm. ...
Exploring sex disparities in cardiovascular disease risk factors using principal component analysis and latent class analysis techniques [0.03%]
利用主成分分析和潜在类别分析技术探索心血管疾病风险因素的性别差异
Gamal Saad Mohamed Khamis,Sultan Munadi Alanazi
Gamal Saad Mohamed Khamis
Background: This study used machine learning techniques to evaluate cardiovascular disease risk factors (CVD) and the relationship between sex and these risk factors. The objective was pursued in the context of CVD being ...
Digital communication and virtual reality for extending the behavioural treatment of obesity - the patients' perspective: results of an online survey in Germany [0.03%]
从患者角度出发的在线调查：德国针对肥胖行为治疗的数字化沟通和虚拟现实技术的应用效果研究
Claudia Luck-Sikorski,Regine Hochrein,Nina Döllinger et al.
Claudia Luck-Sikorski et al.
Background: CBT has been found effective for the treatment of EDs and obesity. However not all patients achieve clinically significant weight loss and weight regain is common. In this context, technology-based interventio...
Risk prediction of heart failure in patients with ischemic heart disease using network analytics and stacking ensemble learning [0.03%]
基于网络分析和堆叠集成学习的冠心病患者心力衰竭风险预测模型研究
Dejia Zhou,Hang Qiu,Liya Wang et al.
Dejia Zhou et al.
Background: Heart failure (HF) is a major complication following ischemic heart disease (IHD) and it adversely affects the outcome. Early prediction of HF risk in patients with IHD is beneficial for timely intervention an...
Digital encounter decision aids linked to clinical practice guidelines: results from user testing SHARE-IT decision aids in primary care [0.03%]
数字相遇决策辅助工具与临床实践指南相结合：初级保健中SHARE-IT决策辅助工具的用户测试结果
Pieter Van Bostraeten,Bert Aertgeerts,Geertruida Bekkering et al.
Pieter Van Bostraeten et al.
Background: Encounter decision aids (EDAs) are tools that can support shared decision making (SDM), up to the clinical encounter. However, adoption of these tools has been limited, as they are hard to produce, to keep up-...