Improving readability of layperson abstracts and summaries in oncology using task-specific large language model powered tool: results from the BRIDGE-AI 7 study [0.03%]
使用任务特定的大语言模型工具改进肿瘤学中非专业摘要和概要的可读性：BRIDGE-AI 7研究的结果
Aalamnoor S Pannu,Ilicia Cano,Ethan Layne et al.
Aalamnoor S Pannu et al.
Objectives: To compare the performance of task-specific generative AI, with general-purpose large language models (LLMs) in generating more readable lay abstracts and summaries (LASs) of Oncology research. ...
Accuracy of administrative data in ascertaining health conditions: a systematic review [0.03%]
行政数据认定健康状况的准确性的系统综述
Alexander C Campbell,Jessica Tyler,Rebecca R Shuttleworth et al.
Alexander C Campbell et al.
Objectives: To conduct a systematic review of studies assessing the accuracy of International Classification of Diseases (ICD) and Diagnostic and Statistical Manual of Mental Disorders (DSM) codes in administrative data f...
Building a consumer health informatics introductory course consensus curriculum: an eDelphi study [0.03%]
利用eDelphi研究建立消费者健康信息学入门课程共识性大纲
Olivia F Krol,Khaya Clark,Phillip D Jenkins et al.
Olivia F Krol et al.
Objective: To develop consensus-based core competencies for an entry-level graduate Consumer Health Informatics (CHI) course using a rigorous eDelphi methodology. ...
A methotrexate dashboard: integrating MTXPK.org into the electronic health record to facilitate model-informed care for pediatric patients receiving high-dose methotrexate [0.03%]
一项甲氨蝶呤检测板：将MTXPK.org整合至电子健康记录中，以促进儿科高剂量甲氨喋呤患者的模型导向化治疗
Zachary L Taylor,Nieko Punt,Chris Jenkinson et al.
Zachary L Taylor et al.
Purpose: The MTXPK.org webtool facilitates model-informed supportive care and glucarpidase use in patients receiving high-dose methotrexate, but its reliance on manual data entry limits workflow integration. We aimed to h...
Comparing risk factors in severe COVID-19 using machine learning and non-machine learning methods: analysis from 2 international randomized controlled trials [0.03%]
利用机器学习和非机器学习方法评估严重COVID-19的危险因素：来自两项国际随机对照试验的分析
Christian Møller Jensen,Ramtin Zargari Marandi,Kasper Sommerlund Moestrup et al.
Christian Møller Jensen et al.
Objective: To compare differences in risk factors and 90-day mortality prediction from 2 machine learning (ML) models with a previously published non-ML model and investigate their validity in an external cohort. ...
Development of the authentication and authorization processes for the iAgree portal, a platform for patient-controlled data sharing across health systems [0.03%]
面向医疗体系的患者控件iAgree平台的数据共享认证及授权流程开发
Spencer L Soohoo,Michelle Sophie Keller,Yunan Chen et al.
Spencer L Soohoo et al.
Objective: To develop the authentication and authorization module for iAgree, a privacy-preserving platform that enables patients to manage consent preferences and share electronic health record (EHR) data across multiple...
Use and characteristics of free/libre and open source electronic health records: an overview of reviews [0.03%]
自由/开放源电子健康记录的使用和特征：综述类论文概述
Arthur Thives Mello,Daniel Henrique Scandolara,Júlia Meller Dias De Oliveira et al.
Arthur Thives Mello et al.
Objective: To synthesize and consolidate the existing evidence on the use and characteristics of Free/Libre and Open Source Software (FLOSS)-based electronic health records (EHRs) in global healthcare settings. ...
A computational phenotype for pediatric asthma exacerbations requiring hospitalization using electronic health record data [0.03%]
基于电子健康档案数据的儿科哮喘急性发作住院的计算表型
Colin Rogerson,Danielle Severns,Jason Stemple et al.
Colin Rogerson et al.
Background: Computational phenotypes can be used to improve patient selection for observational studies. We sought to derive and validate a computational phenotype for pediatric asthma exacerbation requiring hospitalizati...
Expanding the OMOP common data model to support extracorporeal life support research [0.03%]
扩展OMOP通用数据模型以支持体外生命支持研究
Clemens Rieder,Aleh Zhuk,Ahmed Said et al.
Clemens Rieder et al.
Objective: Despite the increased availability of electronic health records, open-source standardized data collection to facilitate high-resolution data during extracorporeal life support (ECLS) is lacking. This project ai...
Understanding uncertainty in large language model predictions of early death in critically ill patients: a conformal prediction approach [0.03%]
理解大型语言模型在重症患者早期死亡预测中的不确定性：一种符合预测方法的角度
Fatemeh Shah-Mohammadi,Alexander Millar,Julio C Facelli et al.
Fatemeh Shah-Mohammadi et al.
Background: Early prediction of in-hospital death remains a significant challenge due to the limited availability of structured data during initial admission. Unstructured clinical notes, which often contain important obs...