Death risk prediction model for patients with non-traumatic intracerebral hemorrhage [0.03%]
非创伤性脑出血患者死亡风险预测模型
Yidan Chen,Xuhui Liu,Mingmin Yan et al.
Yidan Chen et al.
Background: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage (ICH) using a machine learning model. Methods: ...
Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images [0.03%]
基于小波变换的视觉图像在深度学习分类房颤中的应用研究
Ling-Chun Sun,Chia-Chiang Lee,Hung-Yen Ke et al.
Ling-Chun Sun et al.
Background: As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the condition has become the epicenter of a plethora of ECG diagnostic research. In recent diagnostic methodologies, Morse Con...
Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis [0.03%]
用于预测PTSD的机器学习算法：系统评价和meta分析
Masoumeh Vali,Hossein Motahari Nezhad,Levente Kovacs et al.
Masoumeh Vali et al.
This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-traumatic stress disorder (PTSD) predictive models. We conducted a systematic review and random-effect meta-analysis summarizing predictive mode...
Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions [0.03%]
一种用于术后减肥性低血糖的决策支持系统的研发：在非限制日常生活的条件下进行预测算法开发
Francesco Prendin,Olivia Streicher,Giacomo Cappon et al.
Francesco Prendin et al.
Background: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, characterised by critically low blood glucose levels following meal-induced glycaemic excursions. The disabling consequences of...
Implementation of a Laboratory Information Management System (LIMS) for microbiology in Timor-Leste: challenges, mitigation strategies, and end-user experiences [0.03%]
东帝汶微生物实验室信息管理系统（LIMS）的实施：挑战、缓解策略和最终用户经验
Tessa Oakley,Juliao Vaz,Fausto da Silva et al.
Tessa Oakley et al.
Background: Effective diagnostic capacity is crucial for clinical decision-making, with up to 70% of decisions in high-resource settings based on laboratory test results. However, in low- and middle-income countries (LMIC...
Enhancing prehospital decision-making: exploring user needs and design considerations for clinical decision support systems [0.03%]
增强现场救护决策：探索临床决策支持系统的用户需求及设计要点
Enze Bai,Zhan Zhang,Yincao Xu et al.
Enze Bai et al.
Background: In prehospital emergency care, providers face significant challenges in making informed decisions due to factors such as limited cognitive support, high-stress environments, and lack of experience with certain...
Empowering personalized oncology: evolution of digital support and visualization tools for molecular tumor boards [0.03%]
赋能个性化肿瘤学：分子肿瘤专家组的数字支持和可视化工具的发展演变
Cosima Strantz,Dominik Böhm,Thomas Ganslandt et al.
Cosima Strantz et al.
Background: Molecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is ess...
Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms [0.03%]
基于机器学习算法的肯尼亚儿童腹泻临床预测模型的推导和验证
Billy Ogwel,Vincent H Mzazi,Alex O Awuor et al.
Billy Ogwel et al.
Background: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased ris...
Combining theory and usability testing to inform optimization and implementation of an online primary care depression management tool [0.03%]
结合理论和可用性测试以优化和实施一种在线初级保健抑郁症管理工具
Nicola McCleary,Justin Presseau,Isabelle Perkins et al.
Nicola McCleary et al.
Background: The 'Ottawa Depression Algorithm' is an evidence-based online tool developed to support primary care professionals care for adults with depression. Uptake of such tools require provider behaviour change. Ident...
Causal analysis for multivariate integrated clinical and environmental exposures data [0.03%]
多元集成临床和环境暴露数据的因果分析
Meghamala Sinha,Perry Haaland,Ashok Krishnamurthy et al.
Meghamala Sinha et al.
Electronic health records (EHRs) provide a rich source of observational patient data that can be explored to infer underlying causal relationships. These causal relationships can be applied to augment medical decision-making or suggest hypo...