PhenoSS: phenotype semantic similarity-based approach for rare disease prediction and patient clustering [0.03%]
基于表型语义相似性的罕见病预测及患者聚类方法(PhenoSS)
Shihan Chen,Quan M Nguyen,Yu Hu et al.
Shihan Chen et al.
Objectives: Systematic clinical phenotyping using Human Phenotype Ontology (HPO) is central to rare disease diagnosis. However, current disease prioritization (ranking candidate diseases from HPO for a patient) methods fa...
Tipping the balance: impact of class imbalance correction on the performance of clinical risk prediction models [0.03%]
化不平衡对临床风险预测模型性能的影响
Amalie Koch Andersen,Hadi Mehdizavareh,Arijit Khan et al.
Amalie Koch Andersen et al.
Objectives: Machine-learning-based clinical risk prediction models are increasingly used to support decision-making in healthcare. While class-imbalance correction techniques are commonly applied to address rare outcomes,...
Who is doing informatics work in US governmental public health agencies? [0.03%]
美国政府公共卫生机构中的信息学工作者是谁？
Sripriya Rajamani,Divya Rupini Gunashekar,Umesh Ghimire et al.
Sripriya Rajamani et al.
Objectives: Data modernization (DM) seeks to transform data and information systems in public health (PH) to support core activities. This study characterizes incumbent PH workers who perform informatics and data-centric ...
Real-time EHR secure messaging to coordinate emergency department disposition for 30-day revisit patients [0.03%]
基于电子健康档案的急诊科实时安全Messaging协调以防止30天内再次就诊
Priyanka Solanki,William Small,Jaya Sondhi et al.
Priyanka Solanki et al.
Objectives: To evaluate whether real-time electronic health record (EHR)-based secure messaging between emergency department (ED) clinicians and prior discharge teams influences ED disposition decisions for patients re-pr...
Veteran health information exchange volume and 30-day readmissions, avoidable hospitalizations, and in-hospital mortality: evidence from community and Veterans Health Administration direct care [0.03%]
退伍军人健康信息交换量与30天再入院、可避免住院和院内死亡率：来自社区和退伍军人卫生管理局直接护理的证据
Abbie Zhang,Daniel Lipsey,Stuart Figueroa et al.
Abbie Zhang et al.
Objective: To determine whether a greater volume of health information exchange (HIE) between care delivery systems improves patient outcomes and whether effects differ between community care and Veterans Health Administr...
Characterization and Validation of EHR Computable Phenotypes for Long COVID Using Patient-Reported Symptoms: Insights from the Nationwide RECOVER Program [0.03%]
基于患者报告症状的电子健康记录可计算表型特征和验证：来自全国范围RECOVER计划的见解
Victor M Castro,Vivian Gainer,Nich Wattanasin et al.
Victor M Castro et al.
Objective: Long COVID (LC) remains poorly understood, and there is a critical need for advanced computational tools to better identify and characterize patients. In this study, we use summarized symptom reports by RECOVER...
Medical code embeddings from claims-based co-occurrences: a unified semantic space for ICD-10 diagnoses and ATC medications [0.03%]
基于索赔数据的共现生成医学代码嵌入：ICD-10诊断和ATC药物的统一语义空间
Corentin Faujour,Stéphane Bouée,Corinne Emery et al.
Corentin Faujour et al.
Objective: The analysis of care trajectories derived from electronic health records and claims data has become increasingly common in biomedical informatics. This has enabled large-scale studies of care processes, yet wid...
Translating machine learning predictions into meaningful risk estimates to support clinical decisions: a post hoc analysis of chronic obstructive pulmonary disease adverse outcomes using unified auto clinical scores [0.03%]
基于统一自动临床评分的慢性阻塞性肺疾病不良结局的回顾性分析，将机器学习预测转化为有意义的风险评估以支持临床决策
Anthony Lianjie Li,Moses YiDong Lim,Weixiang Lian et al.
Anthony Lianjie Li et al.
Objective: The successful integration of Machine Learning (ML) models into clinical practice remains limited, as they often lack the standardized, quantifiable risk measures essential for clinical workflows. This study, t...