Dynamic prediction of paroxysmal atrial fibrillation onset using longitudinal sample entropy in joint models [0.03%]
联合模型中纵向样本熵在预测阵发性房颤发生中的动态分析
Nicolas Ngo,Aline Campos Reis de Souza,Roch Giorgi
Nicolas Ngo
Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with a five-fold increased risk of stroke. Early prediction of AF onset could improve care for at-risk patients. Existing predic...
Multiple imputation for missing values in ordinal variables from cancer registry data when performing Cox proportional hazards regression [0.03%]
Cox比例风险回归分析中基于癌症登记数据的序号缺失变量的多重填补方法研究
Anika Kästner,Wolfgang Hoffmann,Johannes Hüsing et al.
Anika Kästner et al.
Use of a self-completed life history calendar in relation to data completeness and accuracy [0.03%]
自我填写生命历史日历的使用与数据完整性和准确性之间的关系
Jennifer Yu,Prevost Jantchou,Rui Ning Gong et al.
Jennifer Yu et al.
Correction: Randomization in the age of platform trials: unexplored challenges and some potential solutions [0.03%]
纠正：平台试验时代的随机化：尚未探索的挑战及潜在解决方案
Olga Kuznetsova,Jennifer Ross,Daniel Bodden et al.
Olga Kuznetsova et al.
Published Erratum
BMC medical research methodology. 2026 Feb 5;26(1):25. DOI:10.1186/s12874-026-02788-2 2026
Privacy-preserving federated prediction of health outcomes using multi-center survey data [0.03%]
基于多中心调查数据的隐私保护联邦健康结果预测
Supratim Das,Mahdie Rafiei,Paula T Kammer et al.
Supratim Das et al.
Closing the loop: Benefits and challenges of sharing clinical trial results with participants after trial close-out [0.03%]
试验结束后向受试者反馈临床研究结果的益处和挑战
Jodi L Gallant,Tristan Paranavitana,Sofia Bzovsky et al.
Jodi L Gallant et al.
Background: Clinical trial participants have a right to know the results of the trials in which they participate. Trial results are often not shared directly with participants and concerns with privacy and resource constr...
Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness [0.03%]
针对小数据集的机器学习性能：随机过采样可以改善数据偏差和公平性
Lin Wang,Elliott Shi,Brett Meyers et al.
Lin Wang et al.
Standardized survival probabilities and contrasts between hierarchical units in multilevel survival models [0.03%]
多水平生存模型中的标准生存概率及各级单元间的对比分析
Alessandro Gasparini,Michael J Crowther,Justin M Schaffer
Alessandro Gasparini
Assessing imputation techniques for missing data in small and multicollinear datasets: insights from craniofacial morphometry [0.03%]
缺失数据的填补方法评价：来自颅面形态测量学的启示
Norli Anida Abdullah,Firdaus Hariri,Mohamad Norikmal Fazli Hisam et al.
Norli Anida Abdullah et al.
Background: Analyses of craniofacial morphology are essential for various medical and research applications, including the study of midfacial development, dysmorphologies, and planning surgical interventions. Incomplete C...
Prediction of recurrent ischemic stroke using machine learning from real-world data [0.03%]
基于真实世界数据的机器学习预测缺血性卒中复发
Noor Haidar Kadum Alsalman,Amani Al-Ghraibah,Siti Maisharah Sheikh Ghadzi et al.
Noor Haidar Kadum Alsalman et al.
Background: Recurrent ischemic stroke (RIS) is a significant challenge in Malaysia, affecting approximately 33% of patients. However, studies using artificial intelligence (AI) to predict this event using real-world data ...